Dear students, in this topic we shall discuss insulin and glucagon hormones produced by the pancreas. Pancreas is a dual gland having exocrine as well as endocrine functions. It is composed of two types of tissues. One tissue is known as the asinus which is exocrine. The other tissues include the islets of Langerhans which are endocrine in function. We shall discuss islets of Langerhans as endocrine tissue in detail. The islets of Langerhans have four types of secretory cells. First beta cells which constitute about 60% of the islets and they produce the hormone in soline. The second type of endocrine cells in the islets of Langerhans are alpha cells which constitute about 25% of the islets and produce the hormone glucagon. The third type of cells are the delta cells which constitute about 10% of the islets and produce a hormone which is called somatostatin. This hormone inhibits the release of both in soline and glucagon. The fourth type of cells are the PP cells. These are very small in number and they produce a hormone which is called pancreatic polypeptide. Dear students, we shall discuss insuline and glucagon hormones in detail in this topic and now we shall discuss, first we shall discuss the stimuli for the release of insuline hormone from the pancreas. The major stimulus for the beta cells to secrete insuline is high blood glucose level. Release of insuline is also stimulated by some other factors which include glucagon, growth hormone, gastric inhibitory peptide or GIP, epinephrine and elevated levels of amino acids. These all stimulate the release of insuline from beta cells. Dear students, we shall now see the effects of insuline. Insulin has major effects on carbohydrate, fats and proteins metabolism. The biggest effect of this is that it reduces the glucose level in the blood. For this purpose, it increases the uptake of glucose by the cells of liver, muscles and adipose tissue. It also stimulates glycogenesis in the liver and muscles. This means conversion of glucose into glycogen which occurs in the liver and muscles. Insulin also stimulates lipogenesis in liver and adipose tissue, the synthesis of complex lipids from fatty acids. This process is also stimulated by insulin. Insulin also stimulates the uptake of amino acids into the liver and muscles. It's the acid, tino, major components and nutrients, on tino's metabolism copper, insulin critical effects. Dear students, the deficiency of insulin causes a disease which is called Diabetes mellitus, which is of two types, Diabetes mellitus type 1 and Diabetes mellitus type 2. The absolute deficiency of insulin, that is, the reduced release of insulin by the beta cells causes the Diabetes mellitus type 1. Diabetes mellitus type 1, that is, the relative deficiency of insulin, that is, because of the defective insulin receptors in the target tissues. This causes Diabetes mellitus type 2. Dear students, Diabetes leads to hyperglycemia, that is, high blood glucose level, glycosuria, that is, urine-may, glucose kaana, reduced ability to utilize glucose by the cell, also reduced ability to synthesize lipids and proteins, moreover, accumulation of non-metabolized fat particles in the blood, which appear as ketone bodies. These all happen because of disturbances of carbohydrate, lipid and protein metabolism, which are actually affected and controlled by insulin. When these three major components of metabolism affect, then the result of these three factors will come into the form of many organs' defective functions. In this, the diseases produced by Diabetes patients are Cataract in the eye, Cardiovascular diseases or Renal, any Good Decay, diseases. Dear students, now we shall discuss the other hormone produced by pancreas, that is, Glucogon. Glucogon is secreted in response to hyperglycemia, the blood-may-glucose level, sorry, it is produced in response to hypoglycemia, when blood-may-glucose concentration decreases, then Glucogon is produced. It increases glucose level in the blood by lipolysis and glycogenolysis and by stimulating gluconeogenesis. In this way, all its effects are just opposite to that of insulin. We call these opposite effects antagonistic actions or antagonistic effects. These antagonistic effects are important in maintaining the appropriate level of glucose in the blood.


Hello and welcome back to War Economy and State. I'm Ryan McMacon. I'm a senior editor with the Mises Institute and with me as always is my co-host Zachary Yoast and this is the monthly foreign policy podcast of the Mises Institute where we just check in and see what regimes around the world are trying to do in terms of starting World War 3 these days and And and that always includes of course the United States regime which is an active player in playing up global conflict But we're we're open to criticizing all regimes equally and so we like we like to give them a close look and and this week we're looking at the antics from both the US government and the Chinese government in terms of balloon hysteria and It has certainly been a big issue since a Chinese balloon of some kind flew over the northern continental United States and Then there were there was basically a freak out in the media less so from the Pentagon The Pentagon's a little more restrained when it comes to actual foreign powers who could put up a fight I've noticed. Yeah, sure the Pentagon's always in favor of invading some Country that can't defend itself though and it comes to another country with nuclear arms and stuff often the the Pentagon is a bit more reasonable and They seem to be somewhat reasonable in this case But the hysteria in the media and among politics are especially Republican politicians in Congress Was just quite over the top and so if you weren't following the story there was this big balloon and It was over the US and then it didn't get shot down till it exited US land space Over the Atlantic Ocean down I believe off South Carolina and then it was shot down and We are supposed to believe that this presented a grave and novel new threat to the American people somehow Never mind the fact of course that China has many many low orbit spy satellites That are functioning as we speak and of course the United States does the same thing so talk about a tiny blip in the whole record of large countries spying on each other Because they can and because they do and have been doing so for many decades but I guess for some reason this big balloon because people saw a photo of it online got people really really worked up about it and We're trying to kind of point out the absurdity of this, but also just how insane it is to just try continually trying to Stir up conflict with the Chinese regime unnecessarily Which by the way should never be confused with pacifism or this idea that armed neutrality has no benefits But the fact of the matter is is that Starting a major conflict with a major nuclear power over something so minor and which provides no reason To suspect that any sort of new or real threat is offered by it Really is just a great illustration of just how sterical Washington is and I think how much they recognize that maybe they can benefit From whipping up the voters in terms of anti-Chinese sentiment But maybe you have a different take on it Zach I mean when you when you watch the Chinese thing Unfold the balloon balloon gate What was your reaction?  This was just a highly visible incident of it And I think it might be how Americans have such a highly moralized view of foreign policy Where it's sort of like a romantic play or something that It's just outrageous to them that this this is happening Whereas if you have a more realistic Conception of how you know the tragedy of great power politics as it were You'd understand well, this is just something that happens and we don't need to go code red I mean one of my friends Told me that he got into a fight with someone at his church because this person thought That in response the US should sink China's aircraft carrier Which by the way is ancient. It's literally a Soviet Union like Fire sale like junk that they actually bought from Ukraine. Okay. Yeah, if you're picturing a Nimitz class aircraft carrier You are picturing picturing something very very unlike the Chinese aircraft carrier. Yeah People were going nuts over this there's spying going on all the time I mean DC's undoubtedly infested with spies including from our so-called allies and friends But sure it's violating US sovereignty so we should shoot it down. I mean like people were complaining that they missed Now they're shooting down, you know anything that moves apparently above a certain altitude and Over Lake Huron apparently they missed with the first Sidewinder missile and people were complaining. Oh It had each missile cost four hundred thousand dollars, which is you know a lot of money But it this all this money shooting down. Who knows what is the best money the Defense Department spent in decades It's actually been spent in defense of ours, you know sovereignty of actual America It's something that occurred within ten thousand miles right United States remarkable And now comes the UFO talk, right? I mean Who knows all that stuff that's up there and this is actually a tactic China has used off and on as you know You just fly a bunch of stuff around and see what happens And actually if the balloon exercise was an attempt to see how the US public would react To Chinese devices in US airspace they collected a lot of interesting data there. I would say I mean who knows They maybe they just did to see let's just see what happens. That's an intelligence gathering mission essentially Yeah, I mean think of how much how many man hours were dedicated to These balloons and whatnot. I mean it took up a lot of finite space and resources of people scrambling around and I mean Also the balloons. I mean it sort of speaks to how secure America is in that our enemies the traditional ways our enemies attack us is with high altitude balloons because in In World War two, I think like the only attacks on the continental US Were Japan floated these balloons way up into the stratosphere with bombs that just randomly fell Like in the Washington Forest or something like so, you know, it's it's not that big a deal I thought it was sort of fun Just you know, oh boy this thing everyone can see but it's not Spying's not the end of the world everyone does it and I think the fact that so many people don't get that speaks to how we just have a Poor understanding of the international system. Well, and of course if when you hear about something a alleged spy device being shot down at high altitude if you follow international relations, of course, you immediately think of the 1960 you to incident where the Soviets shot down an American plane Over the Soviet Union which had a pilot in it who parachuted down and then was captured he was sentenced to for espionage and put in prison where he served two years before a a Trade with some Soviet spy in an American prison and That was that was a whole big deal Naturally wasn't surprising at all to hear that Eisenhower didn't think it was a great idea to fly these planes with pilots in them over the Soviet Union And he was he was correct But you know funnily the the United States First to claim this was a weather information gathering mission Which the Soviets didn't buy And then there was a whole cover-up and of course they were telling the public one thing and you know Just the exact sort of antics That you would expect from any sort of nation-state in this position, and I just always think it's so funny that With when China behaves exactly like the United States either is currently behaving or has behaved that this is some sort of a dastardly deed Unun Rivaled in the history of international state relations, but I guess it comes back to what you say about this moralistic view Toward everything right and I guess it kind of makes you miss the British a little bit at least the British during all their Colonial antics and international meddling. They all did understand. This is this is the game Right. This is what we do to you know deal with our rivals like France and Russia and Turkey and So on and there was a certain detach a moral detachment from it to be sure but yeah Americans everything's moral and so it's and every war is It has to be like some moral crusade and so that just I guess informs every foreign policy decision That takes place within our borders but you raised another issue on this was an interesting legal issue that Is fun to think about and maybe someday will be relevant is What if a state national guard unit state Air National Guard unit had scrambled planes and Shot down the Chinese balloon itself saying hey We just had this we had this incursion in our airspace and we don't know what it was So we shot it down. That's what the Air National Guard is for it was a defensive measure How do you think the Pentagon would respond to that? Well, how would that change the nature of the debate? Yeah, this was an interesting question I just thought of watching the balloon float along when everyone was like why isn't the government shot shooting it down Etc. Etc. And I'm definitely not a lawyer But in my Google law degree The Constitution says that a state cannot quote engage in war unless actually invaded or in such imminent Danger as will not admit of delay So I think it part of the question hinges on whether or not an airspace violation is Would count as an invasion But I also Talking with some friends discovered another loophole where if the airspace violation did not count as an invasion Then it doesn't fall under the federal government's purview Could a state shoot down the spy balloon Claiming that it was violating like wiretapping laws or something and it's like this is not a military operation You know, we are just enforcing our our own laws whereas if it was I think it could be a fun court case You know if it was actually like this was an invasion. We have the right to shoot it down I mean who I doubt the Supreme Court would be super amenable to these sort of states rights state sovereignty arguments, but It would be fun nonetheless Yeah, I think as well established that the constitution doesn't actually care what the text of the cost or that the supreme court doesn't care what the constitution text actually says And what was clear to everyone in the 19th century apparently is like reading Sanskrit today for federal lawyers So You're right, of course That's a great loophole, right if the federal government says Oh, it's a it's a violation of US sovereignty. So we had to shoot it down That would create it would seem the precedent not the legal precedent in the technical sense, but Certainly a political and tactical precedent That oh, well a foreign Balloon in your airspace is an invasion And if it is an invasion then the state national guard Has the prerogative to deal with it. So I would love to see how that would be Delt within court I think would only become an issue in the future as the federal government starts to weaken in power due to massive debt and things like that But uh, yeah, right now, I think there's uh, I don't think it's likely the Pentagon would absolutely freak out I think if the the state national guard informed them that we've sent up some planes to shoot this chinese device And we'll just see what happens Yes, also though it could there would be a I mean it'd be good states asserting, you know They're right decentralization, but there would be the trade-off Of then we'd get all these governors would be posing with like these giant cold war era Flat guns that can shoot up to 40 000 feet. They'd be running commercials like we will defend, you know North dakota from the chinese threat It would sort of be like michael dukakis driving around in the tank except people would be like, oh, yes We must defend the cornfields of iowa from the chinese spying Except the flip side of that is though That's not as dangerous because none of these national guards have the capability of launching international wars. They're taking that is true That's true. Yes. So they're very limited in their capability. Yes So it's kind of like the lithuanian air force Having a parade or something like that, right? It takes 10 minutes Although actually I would probably say that your medium-sized us state probably has a bigger air force than most baltic states But nevertheless, yeah, they don't have really aggressive military capability. Defensive is sufficient in my view But uh, you're right. That would be quite a sight to behold though But I would think the federal government would view that as a big challenge to their power Uh claiming oh look these these state governments now think that they have some sort of role to play in the military defense of the u.s Which of course was the original intent of the text of the u.s constitution But since we nationalize the national guard in 1903, I believe with the nox act We don't believe that anymore. I guess Um, but you're right. I think it would revive that even the I mean like the pennsylvania constitution which has been uh revised since Uh in the last century The the pa governor is like identified as the commander-in-chief of the pennsylvania armed forces And I think it's like that in lots of other places too So it's like I mean it the it's sort of like the legal structure is there for um Some semblance of a case to be made and it also on a sort of funny side note When I was reading about all this I discovered that it's actually been upheld by the supreme court that states can have treason clauses trees but that it's um Basically, it's understood under a legal doctrine that a citizen in the u.s has two loyalties one to the state in which they're a citizen of and to the federal government And in the constitution but also under a regular, you know, they've recognized this in practice The state can you know prosecute someone for treason against the state? And I was very surprised to learn that that's actually how john brown was executed I did not know that but um, no one's been executed for treason against the u.s apparently but uh against the state of virginia They have been so that was amusing. Yeah, I did an article for that on mesas.org looking at the history of basically insurrection and it was in relation to january 6 and it looked at the the existing laws that we have in terms of treason and treason like Crimes and how this is all really a post civil war purely post civil war Invention of any sort of insurrection Or treason charge beyond just what was listed in in the constitution very strictly as actually taking up arms against the united states And part of that was going back to the english civil war like most of the bill of rights and all the good parts of the constitution Because the steward kings were always Broadly defining treason to well this guy did something I don't like so he has committed treason and there was no clear limit on what that meant So they very closely defined in the u.s constitution So yeah part of the reason so few people have been actually prosecuted under that is that historically The law allowed for very little but they created then all of these sort of insurrection related laws Not quite at the level of treason and then you can be nailed for those things um, but the initial idea was that all of the only places that people could have been prosecuted for Trees and were most likely to be prosecuted for taking up arms against the state somehow um Was actually at the state level And yeah shades rebellion Right exactly all that sort of stuff and all those little things that happened throughout the late 18th and early 19th century This was all state-centered stuff But back to the chinese balloon So the uh, uh one thing that I thought of immediately When I saw the whole freak out over the balloon was here we go again now, uh, this was because I remembered back in one And I sent you a funny email about it. I said I said hey, you remember this And you said I well, I think I was in a grade school at the time. So I don't really remember But I was about 24 When the high non island incident occurred and so if you're middle age like me you may remember then that Back on in april of 2001. So this is pre 9 11 A us spy plane was 70 miles off the coast of uh, china specifically high non island, which is very much part of china and uh, so it was intercepted by two chinese planes and They uh, they one of them collided with the us spy plane Uh disappeared pilot presumed dead afterward The us plane however was capable of landing On high non island where the pilots were captured and detained and then of course uh, the bush administration Had to negotiate with them to get these pilots back and all of that and There was they they for the most part de-escalated the situation and were fairly reasonable about it Uh, but remember this is all pre 9 11 to When at the time the us actually when bush had run on and won on a humble foreign policy position And hard to imagine that bush had tried to express that his foreign policy would be about uh limited limited meddling around the world But that certainly changed with historical events After 9 11, uh, but then there was yeah, so there was a whole dust up with that But there was a very much while the the the federal government Responded with some amount of reasonableness If you had a response at the media and in congress very similar To what you have now where he had lots of members of congress just absolutely going bonkers over there How dare how did the chinese intercept our plane that was flying right off their coast? And our spy plane by the way And and then of course the media, you know russia limbaugh those sorts of people just went absolutely bonkers Because you had all these unreformed cold war type conservatives who already in 2001 wanted a new cold war with the chinese back then Which i guess was uh Just to keep china from being less poor. I mean that's mostly what china was focused on back then And and of course boy, how many trillions of dollars of Goods and services. I know we act like we don't export anything around the world But the fact of the matter is the chinese not only you buy a lot of us services, but also invest a lot of The money we give them back into us capital And of course buy us debt which enables the federal government to spend even more On all you people on social security medicare welfare, etc Uh, so that's all that's all due to uh reinvestment of uh dollar spent in china back into the united states Nevertheless, uh for for 20 years We've been hearing about the need for a new cold war in china and so The it just was basically a repeat basically rhetorically nowadays with the The chinese balloon and uh, and then the high non chinese incident The the role i guess was reversed of course is that it was the u.s That was spying very very close to china and of course the u.s has all its satellites going over china as well But it was the same sort of moralistic Uh posturing back then was oh my goodness in attack on a u.s plane is like an attack on oma ha Nebraska And we have to do something about it and these chinese aren't going to stop until they destroy all of our airplanes And uh that was that was a tone back then and of course not surprisingly Lou rockwell had to write articles saying hey, maybe world war three with china is a bad idea and uh, you should think twice about it You write wingers out there um Then of course we forgot about china because of 9 11 for a long time But now it's back and so i guess we should just expect more and more of this as time goes on Right where just every little thing with the chinese is going to be Just one more call For escalation with the chinese How much of that is true in reality and how much of it Translates into actual behind-the-scenes conversations between the u.s regime and the chinese regime That's something people have to keep in mind is that politicians will play up their belligerence Toward foreign regimes a lot for public consumption because they know the public Likes to go bonkers about hating on foreigners, but then what's out of sight is These politicians saying hey, you know I i have to pretend i hate you for the hay seeds back home But you and i of course know that we'll get along just fine as these as two regimes that have to coexist in the world That doesn't mean of course the u.s is going to retreat from Its positions in east asia, but i think You probably would expect that behind closed doors the u.s is going to continue to tell the chinese the regime that like look You know, we know you're spying us We're going to continue to spy on you, but we had to shoot it down For the case of the public and then make a big deal out of it But we'll just go from here and that's probably closer to the reality But i think that the more the public presses on this issue the more it could really produce i think An actual overreaction that could cause real problems at some point in the future Yeah, um, yeah, i thought it was bad that the u.s cancelled a high-level diplomatic talk with china Because of the balloon incident Whereas i think you know If the public was sufficiently macchio-vellian in the good sense They would just see that this is what happens And i think that it it might be helpful to talk about like why all this spying happens and it's not just between supposed foes You know china and the u.s But i mean I think one of the only actual treason convictions In u.s history was against um jonathan pollard who worked for one of the intel agencies who was convicted of spying for israel You know quite a different reaction uh, um to uh To that back then versus now with china, but it's like what is real there are friends Why would they spy on us? It's like it's guaranteed all of our nato allies have spies in dc and whatnot And it's it's because of the radically uncertain nature Of the future which is sort of a core, you know realist a fundamental Assumption about the world. We don't know what the future holds and there's a very good quote from charles de gaulle, which is um States do not have uh states have no permanent friends Only permanent interests, you know, so Who's your friend today might not be your friend tomorrow? I mean there's very If any of the viewers have ever watched, um Yes prime minister. It's hilarious 80s british sitcom The prime minister. I can't remember exactly the context, but The guy is explaining to him, you know, we must be prepared to face our true enemies and he's like the soviets No, the french, of course You know, it's like the soviets are just an interlude in our, you know, 1000 year long feud with the french And it's like, uh, everyone spies on everyone because we need to know information We don't know what other people are thinking and it's why the world is risky Why there is the tragedy of great power politics is even if a state is Building up militarily purely for defensive reasons. There's no way That any other power can know that for sure And so they feel threatened and then they build up, you know, and hence, you know the unhappy Fallen world we live in But so it's just spying happens Sure, we should not like be oh there goes, you know Chinese spy plane or something But You know, we should just recognize this is as normal as you know You know people stealing from the grocery store. It's it's not good But it's just a fact of life that happens and grocery stores Have learned to deal with it and We just need to, you know, it happens. We don't need to, you know You know set up a guillotine to execute shoplifters just because it's a fact of life Shoot to kill everyone who breaks the law Yeah Yes, this is of course a very important point is the uncertainty, right and you can see this Uh in how uncertainty Often leads to unnecessary conflicts It's it's not just that uncertainty makes people afraid and so they're unwilling to enter into conflict Um that maybe could be an issue but very often Other states are often overly confident about their abilities Or about the defense of other states. This has been historically an issue. So This is in many cases states have started wars With an unrealistic view of their relative power and capability Relative to other states because they just didn't know the size of the economy of the other state Um, they didn't understand maybe Just how much another state was willing to put up a fight for a long period of time and all of those sorts of issues And if you think if you miscalculate and think those things are low that look they're going to give up immediately And then you start a war and it turns out they weren't willing to give up immediately Or that they had economic and military capabilities that You weren't aware of Now you've started a completely unnecessary war that you had no chance of winning and so You can see why why everybody's going to want to spy then in those cases There might be an off chance That oh, you only need to build up your military power So much in order to be on a par or have true defensive capability against state x And how do we know this? Well, we need to send in some spies to maybe get a better idea of what the other state's capability Is or if you're an aggressive state you want to send in spies and say hey, can we get it get away?  We better not try We better not start a war with them. Well, that's that's all to the good then if That sort of information flows in a way that it prevents conflict and One way that actually worked And one of the many instances where the cia was just so pathetically wrong was when They continually Reported that the soviet economy was a powerhouse And was just amazing and you can look at some of the the ridiculous Ways that the the soviets try or that the cia tried to measure the soviet economy. It was They just looked at the amount of dresses in department stores and things like that And some some critiques by econops have come out on this noting that the cia had no concept of Like different hetero genius nature of quality In goods and services So they just counted the number of items available in different item classes and didn't look at the equality And recognizing that everything that the soviets had was just a crappier version of what the americans had Right because their economy was garbage So there was this huge overemphasis on what the soviet economy was like now on one level that Prevented the u.s. From being more belligerent than it was to the soviets on the other side There was a downside because it continually fed american hysteria about a missile gap in our inability to deal with an aggressive soviet union so It's hard to predict how a lack of information will play out But yeah, not only does everybody want spies for that reason But how do you know your spies are actually even collecting reliable information? And so it's just it's just with anything right industrial espionage You don't know what's going on with your competitors and you're just trying to get some info and you never know if it's good So it's not going to end not going to end anytime soon And also doesn't really provide a big threat either in terms of with the united states so far ahead Of everybody else in terms of military capability other countries knowing to what extent the u.s. Is far ahead of them Provides no threat to the u.s. All it does is reiterate the fact that the u.s. Has thousands of nukes uh, and it has a nuclear triad and it has immense defensive military capability it may find out that The u.s.'s ability to maybe wage war in eastern europe is not that great Uh, but in terms of defending north america, I think all they're going to find out is that oh, yeah Trying to send a flotilla across the pacific ocean to the west coast of north america probably is not a winning strategy Right.  That's almost entirely theoretical And I mean you can make the argument that missile defense actually is destabilizing because if one country thinks Oh We can't Issue a second strike. We have no deterrent against the u.s. Or whatever Then it leads to this sort of innovation. I'm like, oh, we need a hypersonic missile and things like that So I think it's sort of I think missile defense is also another issue that's driven by Public, you know outcry of do something do something itis, you know, and it's just sort of spying You know the ability to nuke the united states. These are just facts of life that We have to live with and you know We can be calm and collected and things will Be fine most likely most likely right and Back to that point of how many nukes you got I mean, you may disagree But I don't think I happen to agree with the school of thought that you just don't need that many for deterrence So if the u.s. Has 5000 nuclear warheads ready to go That's probably about 4,900 more than it actually needs to provide deterrence And so yeah the some hypersonic missiles when you have a nuclear triad Moving around where two-thirds of that is moving around all the time. I mean, it just means nothing But it's a similar thing then to the spy thing But if you're not paying attention To international relations ever until something is on the front page Of the online newspaper Then it seems like this is some new amazing threat and then people freak out because they're just not otherwise Paying attention so they don't know about all that white noise that's going on in the background constantly So this seems like something new and threatening And they and it's amazing to it at the threats they will ascribe to the chinese regime When you consider the size of the american regime and its ability to violate rights of americans So americans are spied on every minute by their government Are open to all sorts of federal prosecutions at any given time We've seen what happens at places like waco and all of that But oh the real problem is the chinese regime because they might take a picture of your backyard So much worse than what the fbi might do with its latest fiza abuse Against your fourth amendment rights So it's quite remarkable what people are prioritizing there And i guess that's one of the biggest downsides of nationalism and i think that nationalism as a threat is way overblown But one of the real problems with it is that it does tend To have people just ignore what their own regime is doing against them and focus laser like On what foreign regimes are doing out there and then encourage greater power be handed over to Uh, quote-unquote our regime what they view as somehow an organization that that is their friend Um in the name of fighting some foreign regime, which may not wish them well either but Has nowhere near the capability of actually violating their rights the way the domestic regime does In most cases and so that seems to be just a dynamic here As well with the the threat of chinese spying being held up as far far worse than whatever it is The u.s regime is doing Against the bill of rights at any given time. So that's just a dynamic. We're stuck with for now as well Yeah, it's sort of the like the that the part of sometimes people arguing favor of sanctions unlike i ran and stuff as if we squeeze the country that people will stop supporting the regime it's also the same logic behind at least part of The argument for strategic bombing campaigns Is you know, oh, well just the level of the city and the people will rise up against their government and historically You know, it's like never happens the people rally around the government Um and and and on the spying thing I can't remember when it happened now It was like eight years ago Maybe or something but there is a hack into the federal government like personnel database I think it might have been by china or something but it's like The government got all this information on like all these people who work for the federal government because it was the federal government's information on the people, you know sort of uh, you know Ironic in a sense now.  I think is uh, is part of the fun of keeping track of these sorts of things and we do our best to try and prevent Things from getting out of hand but that's a problem we just have constantly with our readership because We do have a significant overlap with the conservative audiences And especially some of the more old school conservatives have still not kind of come around to As you and I have with the restraint school with the realism, they're still heavily even among conservatives Just all these notions of international liberalism and humanitarian interventions and the us is Shining city on the hill and all of that stuff that old stuff dies hard And from what i'm seeing it's at least among the the older age cohorts hasn't gone anywhere Given the amount of criticism we get anytime we run an article at mesas.org promoting peace instead of constant escalation, but With that we better wrap up this episode here of or economy and state Thank you. Zachary for joining me again this month We'll be back next month with a new episode depending on whatever's going on then and so we'll see you next time


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So I've been playing guitar for a long time and I've accumulated quite a few instruments here. This is my current selection from my Guitar closet. I'm going to go through some of these in this video and open these cases up show you guys what I've got Talk about the stories behind some of my favorites And maybe I'll plug a couple of them in and play a little bit and show you what they sound like And maybe we'll see if we can get that one right there to work. It's been a while anyway stick around All right, so first up one of my favorites. This is a regal parlor guitar from 1940 something best I can tell I've tried to Look it up. If anybody has the information about this, you know, please let me know in the comments But this is a cool guitar, I think it still has the original dust on it Just kidding about that Some of my instruments are a little dusty. I just moved to a new place And I hope you had to kind of go through the full the full cleanup, but you know this thing Really good sound to it You know, it's a parlor guitar, so it's kind of a three-quarter size. Maybe not completely in tune But anyway, this is a cool one. I got this at Forest York's guitar shop in Murphy'sboro, Tennessee several years ago and It's in really good shape. It's got a few like beginning to have some little stress cracks here on the back and and You know, it may have had a couple of repairs here on this bridge This doesn't really look like the original bridge obviously, but But yeah, I love this guitar. It sounds great, and I've got a few other videos on the channel of me playing this Out in nature and playing a few songs on it. So you guys should check those out, too Anyway, let's move on to the next one So in a previous video on my channel the Jazzmaster comparison between the classic vibe Squire and the Ventera 60s I mentioned that I've had a lot of inexpensive Squire type guitars in the past a lot of experience with them and this is one of them. This is a Squire Tele This is like a the Butterscotch a Affinity model that they put out a few years ago And I think this was like a hundred bucks or something and it's super light Which I really really liked about it and I replaced the pickups with some, you know much more expensive Pickups, I'm not really exactly sure what they are Rod off, but they were some like, you know, Nashville hot one on Telecaster something and I changed the pickguard out to be a tortoise shell because I really wanted it to be like a Prince Telecaster and Obviously, it's it's filthy and it's still slack detuned from my my recent move but I need to get this thing cleaned up and put some new strings on it and Give this thing a shot again because I really enjoyed playing this I played this on stage for many years. It's great having Squire guitars as long as they play well on stage because if something happens to them and they fall off a stand It's not that big of a deal, you know, you can they're usually pretty tough This one's taken many many falls But anyway, that's kind of my my Prince copy Tele but also my my Nashville twanger, I suppose so Anyway, there you go So another inexpensive guitar that I bought purely for travel and for stage is this Gretch Electromatic so what that is electromagnetic You know, it's a little heavy. It's a solid body Gretch But it really, you know, it has these the pickups the whatever they are TV Jones style Gretch Electro something or other pickups, whatever they're called, but they kind of have that sound They're really kind of a good rock guitar and you know, this guitar is like a hundred and fifty bucks or two hundred bucks tops Probably depends on where you get it or you can get one used and it plays great I Bought this because we were doing some traveling with a band up play in and I needed to go to Canada and Some other places and I needed a cheap guitar I could take in a gig bag that was likely replaceable at a local guitar center if I needed to and You know, this this was okay. This this plays You know, it played good enough for those handful of shows that we did. It was a very rock oriented set and You know, this one fell off the stand a couple of times face flat right before we played and I just picked it up and it was still in tune and You know, so there's something to be said for inexpensive tough guitars like this, but anyway, that's a Gretch electromagnetic Pretty cool. I really like it. All right, this next guitar is one that I have actually never seen one exactly like this was a prototype guitar for a Nashville Nam show, I believe by J. J. Tercer, can you see that there? And yeah, I know all my my guitars are very very dusty and I'll tell you what if I get 100 likes on this video, I will Clean all of them. I promise and oil all of the necks and get all of them very nice So everybody make sure you watch all the way to the end of this one and give it a like and subscribe if you like this Type of stuff for any other other stuff on my channel Anyway, this is a cool Resonator, yeah resonator guitar Got this biscuit cone in here and It's slack tuned currently once again from the move, but I'll tune this one up in a few minutes And maybe play a little bit on it has a great sound finger picked And the pickups don't sound bad. The bridge is very, you know You know tinny kind of bridge sounding obviously, but this lipstick and the neck really has a great sound to it And you can get some jazzy tones out of it, you know considering it's a resonator guitar I'll put this one on stage a few times And it it looks great obviously because it has the big shiny biscuit and so when the lights hit it You know it reflects off into the crowd But anyway, it it's set in a window at NAMM in the sun And so it kind of naturally yellowed through all of this so it looks like it's really old although this is probably like a 90s Anyway, Jay Tercer They make several other guitars, but I've never actually seen this particular one in any other pictures online But if you know anything about it, leave me a comment. Let me know something more about it. I would love to learn more So this is my epiphone es 295 special edition Scotty more model I believe it is and See the epiphone there this one has Custom or sorry replacement Gibson tuners and replacement Gibson P90s I think everything else on it is pretty well stock Saw this thing hanging in For Shorq's guitar store It was his own personal guitar that he had fixed up and decided to get rid of from his large collection And I was in it with my wife and it was our anniversary and she really liked it and said you should buy that and I said I should buy that and so I did and It has the nickname of C3PO or Star Wars family. So This is this is C3PO. I'll definitely plug this one in and play this one in just a little bit Once again, that is a ES 295 believe it says Sounds fantastic, especially with those different P90 pickups very very hot All right, so every guitarist has to have a Stratocaster of some kind This is mine. This is my oldest guitar. I have worked on it a lot I've changed The pickguard and the pickups multiple times The only thing really original You know is the neck and the I guess the tuners are probably original But this is a Fender Japan Stratocaster When I was a senior in high school, I could have bought us a class ring as lots of my Classmates are doing but I chose to take the money and go to the local music store and buy a guitar anyway because I thought that would last longer and Funny story, they all had their class rings stolen at something else some event They were at they put them in the lockers and somebody stole them and unfortunately, but I still have my guitar So, you know, I think I came out the winner on that one But I almost never play this anymore. It's it's mostly just memories and if I really needed a Strat sound I would pull it out and tune it up, but I have so many other guitars It doesn't get a whole lot of play, but anyway, very sentimental to me. I've had it for a long time 20 plus years probably Fender Stratocaster, here you go the Epiphone Casino, this is a 90s model Epiphone Casino Very light obviously the pickguard I've removed it almost immediately This is my number one guitar my favorite guitar of my history in fact I have the serial number and the f-hole from this tattoo to my arm such a memory when I was in the the band in the Mid 90s or so when we made our second record we had a budget to buy some instruments and So this was mine So I got to go down to the Epiphone factory in Nashville on Massman Drive And they had a rack of these different colors and I played them and I picked this one this was my favorite one and I've played it on most every album that I've been on since then I've played it You know numerous shows I've played it on TV This is my this is my guitar that up would potentially run back into a burning house to grab I'm just kidding on that one. I would let the insurance take care of it, but At any rate it may not be super valuable on the marketplace, but it's super valuable to me anyway There you go Epiphone Casino Guess I should show my old-school strap buttons here got my spiderman face a run DMC button Sure, if you can see that hopefully that's coming through on the camera But anyway, love having some buttons on my strap there Yes, the Fender Jazzmaster Ventera for doing a couple of videos on this guitar on my channel So, you know if you're interested in more detail review You can see that I just did a one-year later review on this guitar This is my current favorite guitar not to take anything away from the Epiphone Casino, but you know This is the one I'm currently playing the most Fender Jazzmaster Ventera medium-gauge strings on this one most people me think that's a little heavy, but You know, I kind of like it it adds a little more chunk to the guitar. I don't play a lot of lead on this It's mostly rhythm and and jazz type stuff. I Mean, I don't know. This is a guitar or not, but it has six strings. It's a Pirellas Ben Jotar Kit Joe, I don't know whatever you would call this, but it has six strings and Snarehead like a banjo and It's currently only has four strings on it is tuned up like a ukulele But it has a time had six strings on it This one has a small crack in the headstock here And so I hesitate to tune it all the way up to full concert pitch I usually do like a step flat or something just for the sake of it But you know, that's a pretty cool looking little instrument there play this a lot on the With the tinder innards band could have a bluegrass country band. Maybe I'll put a link in the description for some of that Music, I think there's some videos out on YouTube anyway, weird instrument And this is a dental electro baritone guitar. I'm not really doing my basses or my Slide guitars in this video. It's just normal six string guitars, but this one does have six strings Den electro baritone. I think I got this for 200 bucks used or something It was in the shop and I saw it week after week and and I was bringing one of my kids in there for their Music lessons or their band practice or something and I was like, okay if that guitar is still there at the end of the month I'm gonna have to just go ahead and get it and it was there And so now I have a dental electro baritone. This thing sounds really cool I've done a few tracks for some YouTube videos with this Kind of run through a semi distorted kind of swampy guitar Sound and I'll probably do a video just about this one pretty soon I see that people like baritone guitars these days and this one certainly has a Unique sound to it with these lipstick pickups. So maybe get my silver tone amp out and get this thing plugged in and See what? So we can do Cool, you might dental electro baritone All right, so I guess if you've stuck around now you get to see this thing this DG 20 There's been a few videos about these guitars out Not a lot of them are working these days. I think this one is working when last I tried I'm going to see if I can get it plugged in and Make some sounds come out and maybe I'll do a secondary video on that It's missing a string. I think I may have a replacement string for this in a box somewhere I need to go through and dig I acquired this guitar from the band self and It may actually technically not be mine. It may still be the Halfies, but at any rate I have it Matt if you want it, let me know I'll send it to you But until then I'm gonna see if I can get it working. They use this on the dysmontry album. That was a toy album Anyway DG 20 pretty crazy looking guitar. These are pretty cool sounding but very difficult to play Unless you just want to kind of do some power chords or single note stuff cool Well, thanks for watching my video about all my guitars and I hope you enjoyed it You know leave me a comment if you having me to say about any of these or if you have any questions or Know some extra details that I might want to know that I didn't share in the video about some of these models I'd love to hear it. Love to know. I've got lots of great comments on my previous guitar videos Anyway, hope you enjoyed it. Give it give it a like subscribe if you like Have a good day


Hello and welcome back to EsmerKonf 2023. This is the fifth presentation session of EsmerKonf focusing on quantitative synthesis part 2. As always you can ask questions via Twitter by following at ES Hackathon or by using Slack if you've registered for the conference. Presenters will be online during this session and after to answer your questions. So do keep those questions coming in. So our first session today is by Daniel Heck who's going to be introducing MetaBMA Bayesian Model Averaging for Metronalysis in R. Over to you Daniel. Yeah, hello, my name is Daniel Heck from the University of Marburg and today I will present the R-Package MetaBMA which can be used to perform Bayesian Model Averaging for meta-analysis and the example here concerns the effectiveness of descriptive social norms and more specifically the question how we can make hotel guests reuse their towels and the control group the hotel guests were simply told please reuse your towels because it's good for the environment and the treatment group they were told that actually a majority of guests reuses their towels and the effect size here in seven studies was quantified by log odds ratios on the x-axis and positive values mean that the treatment was effective so that actually the descriptive social norms increased the reuse of towels and the question we have now is how can we accurate the results here from the seven studies and in meta-analysis there are two standard models which are commonly used the fixed effects model assumes that each study has the same constant true effect size mu and That this effect size is identical in all studies the random effects model in contrast assumes that each study has a different effect theta i which varies according to a normal distribution across studies so first the studies are sampled essentially from the normal distribution as shown on the right-hand side and the parameters of this distribution are mu the average effect size and Tau the standard deviation of effect sizes and this tau is also known as the heterogeneity It's amount of differences of effect sizes across studies Now the question of interest are two fold First we are interested in the question whether there is an effect So whether the overall effect mu differs from zero and the second question concerns heterogeneity Specifically is the heterogeneity. So it's tau larger than zero and if you combine these two aspects into models You get four different models which are denoted here by an H for hypothesis H zero is the null hypothesis and H one Alternative and the F is for fixed and there are for random And then you get the four models where you assume either the effect is zero or not and second The heterogeneity is zero or not and the question is obviously which model should we pick? If we select one of the four models we ignore uncertainty Which of the four models is the correct one? And so it might be better to actually consider the uncertainty, which is the best model and Exactly this is done by a Bayesian model averaging So first you have to define prior model probabilities, which is the question How plausible is each of the four models before you see the data and here you seen illustration where they are uniform priors use so on the top there these four boxes for the four hypothesis and Each has a probability of 25% What follows from this is on the bottom on the left and right hand side and the plausibility of our questions First is an effect. Hmm. If you combine the null models and the alternative models, you see it's 50 50 We don't know yet. This is why we do the meter analysis on the right hand side You see the heterogeneity and there you also combine models But on the left hand side the fixed ones and the right hand side the random ones and here it's also 50 50 Now if you collect data the Probabilities are updated. So we now have posterior model probabilities and these are determined essentially by the data We collect these inform the estimation by the prior model model probabilities And as we will see later by the prior distributions on the parameters mu and tau Now what happens is here that the models under the alternative become more plausible They have larger posterior probabilities as indicated by probabilities of 40 percent and 735 percent And if you now ask is that an effect then their combined probability is 75 percent Compared to only 25 percent for the null models. This indicates some evidence that there might be an effect While you consider uncertainty Whether effects vary across studies and the same can be done on the right hand side for heterogeneity and This is what the inclusion base factor quantifies. How much evidence is there for a non-zero effect? So whether mu is different from zero and this is done by comparing two models the alternative models against two null models And thereby we account for the uncertainty Should we assume fixed or random effects and the same you can do for the heterogeneity just that you bundle together different models So here you compare the random effects models against the two fixed effects models however this only works in a Bayesian framework if you assume prior distributions and Specifically this means you need to make assumptions. What size of effect do you expect and how much heterogeneity do you expect and Here these prior distributions are illustrated for the fixed effects models So you see on the right hand side two plots where there's just a point mass at zero So essentially the fixed effects models assume there is no heterogeneity. It's zero on the left hand side It differs between the null and the alternative model whether you assume an effect the null model assumes no effect And the alternative assumes that the effect is likely between minus two and two with higher probabilities assigned to smaller effect sizes And now I switch to the random effects model And you see on the right hand side now a prior distribution on the heterogeneity tau on the standard deviation of effect sizes and This year's the default prior used and based on a literature review Now what are the basic functions of the package you can specify priors you can fit models you can average Across the models and you can compute these inclusion base factors. I mentioned before these are essentially the components I mentioned already and all of these four steps are combined in a single function called meter BMA and Here see how this is called Essentially you have four lines where you specify the input This is a standard input for meter analysis as you would also do in other packages And then you have to specify a prior for the overall effect size here And here you see it's a normal distribution with mean zero and standard deviation point three truncated at zero and On the bottom you see the prior for the heterogeneity The output is rather large. There's a separate tutorial video that explains all of this But essentially you get base factors you get model averaged and results posterior probabilities and estimates for the parameters The plotting functions are very helpful because they show what happens here Essentially you have a posterior for the fixed effects model, which is violet a posterior for the random effects model Which is dotted and red and the model averaged one is in between It's a blue one which is kind of a combination of these two and how far they are combined depends on the posterior probabilities of the models Here you see also a forward plot where you have the descriptive effects as circles and as triangles the shrinked Estimates for the studies and you see that there's quite some shrinkage going on so the model Estimates that the effects are rather similar even though descriptively the effects vary much more on the bottom You also see the three estimates fixed effects random effects and the average one, which is a combination of both So what are the benefits of this approach? I think it's very nice because it's principled the assumptions are very transparent and we consider the uncertainty regarding auxiliary assumptions and You can do it sequentially so you can continuously update your beliefs as more studies are published This is shown here so on the x-axis you accumulate studies You can update your meter analysis and this is what usually happens is that more and more studies come in However, it could be criticized that we consider the fixed effects model at all However, this is a plausible model and for instance if you perform direct replications There's some evidence that this model is supported and only also if you only have few studies You might not have sufficient evidence to for heterogeneity It might be better to assume that the effect is Identical to get a higher predictive accuracy, which means on the bias variance trade-off That you have less variance in predictions And this is beneficial compared to fitting a complex random effects model and of course there are priors And the question is how to pick these you could ask experts with prior elicitation You could do literature reviews and of course you should perform sensitivity analysis to make sure that The results are robust for different priors and of course it's possible to pre-register the priors So thanks for your attention. Thanks to my collaborators at the University of Amsterdam And if you're interested in these topics you can look up four main papers at my web page One of the first concerns the meta packet meta BMA package itself. The second is a primer on the methodology There's a tutorial on chess but you can use these methods in a point-and-click interface And also we applied these methods to a set of pre-registered pre-registered replications. So thanks a lot and see you around Thanks so much Daniel up next we have Jens von derich who's going to be introducing Metapype X data analysis and harmonization for multi lab replications of experimental designs Yeah, thanks for joining us today everybody I'm going to present the metapype X framework today Which is for data analysis and harmonization for multi lab replications of experimental designs This will be more of a brief introduction how we arrived at the framework what it is and how we'd like to see being used and For a bit more details on how to actually use it please Feel free to attend our tutorial on Friday at this year's as my content as well So where did it start? we were going to reanalyze data from large-scale direct replication projects like the many labs or the multi lab registered replication reports and We intended to use participant or item level data And we needed that data to be cleaned in order to compare reanalysis with already published results That turned out to be much more difficult than we anticipated But before I'm going to talk about the difficulties I just want to get some vocabulary out of the way to make sure that we're talking about the same things So this graphic here represents the basic structure of multi labs and Say multi labs. I just as I just said mean like the multi lab registered replication reports on many labs And all of these have a very similar structure on some level And the first interpretable data would usually be item level data where each participant is a row and each item is so represented as a column and For individual participant data these rows are still participants But now the dependent variable has been aggregated to a single numerical value And these again are aggregated to achieve replication level statistics like between group effect sizes or group variances and then those replication statistics are used to run meta-analysis to aggregate data for each replication project and Finally a multi lab then might Might span multiple of these replication projects Yeah, but despite the very similar structure and the solutions they found To document and analyze their data were rather unique. So just a few examples here The Software and use was usually are but sometimes as PSS or other software the code structure itself was very unique to each multi lab so When or by who is data aggregated sometimes these steps were taken by the replication sites and we don't find the actual raw data And sometimes that was done at the replication project level Yeah, and the data files themselves are very different sometimes CSV files as PSS files exo files are data, etc And if you include the files with information for the data transformations, so like information that and the code sources the analysis or data transformation code sources You will also find solutions like text files or Google documents And probably some more Um Yeah, so the variation across the multi labs is quite large There is little consistency in naming conventions sometimes the verbal descriptions and other provided details On the data transformations are sparse or even inconsistent Some of the code solutions are really complex though interesting And sometimes we do not find cleaned datasets at different levels of aggregation So this just results in a lot of detective work for anyone who wants to use that data and Makes computation and reproducibility much harder to achieve and actually check Yeah, and I want to Elaborate a bit more about computation reproducibility But that we mean you can run the original code on the original data and achieve the same results as reported by the projects And there were a few great analyses on registered reports and publications with open data badges over the last couple of years But the results are somewhat devastating to be honest Which maybe just means it's it may be a lot harder to get there than we think about than we think So some of the results were just only about 30 percent of the articles these Projects looked at were actually reproducible The computation reproducibility depends on the skill level of the analyst, which then again Posed the question like how much skill is necessary until it's not computational reproducible anymore Most of these analysis agreed that using non proprietary formats helps a lot and providing version control So that could be using solutions like our end but also using containers and Like Docker for example, and also just simple stuff like using relative locations. And so You have to change less Less file paths just when you're trying to rerun it And some of these were already implemented Some of these best practices were already implemented in some of the multi labs So for example many labs to found a package a solution for their data transformations You know, I think the the package at the moment could be pulled. I'm sure if it's available right now There were container solutions a lot of non prior non proprietary software was used And also bug trackers, which are great just to make sure that the community interacting with those projects is visible and Just so we know where people have found errors or deviations Yeah, but this is very inconsistent across these projects So so our solution to these complications is Meta pipe X and just to break down the name quickly is a pipeline from meta analysis of experimental data And these make up more than 50% of the currently published director application multi labs Yes, the framework consists of three components We see on the left the standardized analysis pipeline, which provides guidance to make the analytical structure more explicit And reduces documentation effort. We also created an R package that matches this pipeline So it analyzes data it creates standardized documentation for the data at different levels of aggregation and the third component of the framework is a shiny app, which we can explore data Which we can use to explore data Meta pipe X data, that's a combination of replication results and meta analytical results and basically is just a GI to Select and visualize multi lab analyses. So You can also run the analysis within the shiny app and Combine different data formats. It takes SPSS data R data and CSV files So you don't have to be able to work with R to implement the pipeline. You can just use this GUI and the most comfortable version to apply the pipeline is the full pipeline function Which just takes individual participant data as an input. So it's depicted on the left and Yeah, then just runs the analysis and creates a full documentation of the standardized pipeline On the right, you see the full structure that is exported by the function and in R This is also provided to you as a nested list With each folder, you always have the data file and According code books, so you can make sense of the columns in the data set And finally what we hope meta pipe X may do We hope it will reduce effort in analysis and documentation We hope it makes your multi lab data more explorable. So no matter if it's your own data are you blind or simulated data? And we hope this fosters interaction between the research community and these types of project Best case scenario it helps to make the multi lab format more accessible to primary researchers and students alike And it helps to develop and ask more meta scientific questions chat more light on questions around heterogeneity Yeah, and that just adds to the meta scientific toolkit Yeah, that's it from us or for me today, thank you for your attention and please feel free to Join our as my com tutorial on Friday Thanks very much Jens next up today We have James Pustiovsky and mega Joshi talking about clustered bootstrapping for handling dependent effect sizes in meta analysis Exploratory application for publication bias analysis over to you James and mega Hi Thanks for joining us for Esmar come 2023. My name is James Pustiovsky and with my colleague mega Joshi We'd like to share one piece of one of our ongoing projects Developing new tools for investigating selective reporting in meta analysis of dependent effect sizes The method that we'll be demonstrating today is a cluster level bootstrap for a vavae hedges type selection model Now by selective reporting we mean the phenomenon where statistically significant Affirmative results are more likely to be reported and therefore more likely to be available for meta analysis Compared to results that aren't statistically significant or aren't consistent with theoretical expectations So this happens as a result of biases in the publication process on the part of journals editors and reviewers As well as because of strategic decisions on the part of authors selective reporting is a big deal It's a major concern for research synthesis because it distorts the evidence base available for meta analysis Kind of like a funhouse mirror distorts your appearance It leads to upward biases and estimates of average effect sizes and complex biases and estimates of heterogeneity All of which makes it all the more difficult to draw conclusions from a synthesis Now a meta analyst might say we've already got tons of tools available for investigating selective reporting Why do we need more? We've got graphical diagnostics like funnel plots tests and adjustment methods like pet peas Selection models p-value diagnostics like p-curve and p-uniform The problem is very few of these methods have been extended to handle dependent effect sizes Which are a really common feature of meta analytic data Dependent effect sizes crop up all over the place For instance when primary studies report results on multiple measures of an outcome construct or measure effects at multiple time points or involve Multiple treatment groups compared to a common control group and they also come up in meta analyses of Correlational effect sizes where you may draw more than one correlation coefficient from based on the same sample If you've done meta analysis work in education psychology or other social science fields You probably recognize that dependent effect sizes are really really common Although we have good methods available for handling this sort of dependency when conducting summary meta analyses or meta regressions There are very few methods available for investigating selective reporting that can accommodate dependent effect sizes And what's more if you use existing tools that don't account for dependency You can get misleading results like two narrow confidence intervals and hypothesis tests that have inflated type one error rates So we want to explore a rough and ready pragmatic strategy for investigating selective reporting while also dealing with dependent effect sizes Our thought is to fit a regular selection model as implemented in the metaphor package And then use a cluster level bootstrap to account for the dependency and this uses standard methods that are implemented in the boot package For demonstrating this method We'll use data from a recent meta analysis by layman and colleagues that looked at the effect of the color red on Attractive judgments the data include 81 effect sizes from 41 studies And so we've got effect size dependency issues to deal with Here's a funnel plot of the data a basic random effects meta analysis indicates an average effect of about point two standard deviations and Substantial heterogeneity of about point three two the funnel plot definitely has some asymmetry to it So you might well be concerned about selective reporting bias with these data Hi, I'm mega and I'm going to go over how to cluster bootstrap selection models To implement a cluster bootstrap using the boot package We need a function to fit the selection model which takes in a data set with one row per cluster The function also has to have an index argument, which is a vector of row indexes used to create the bootstrap sample and Then it can include any further arguments Our data set has one row per effect size and potentially multiple rows per cluster There are at least two ways to turn this into a data set with one row per cluster We can use the group by and summarize functions to create a data set with just cluster level IDs And then we can merge it with the full data by study to get the effect size level data Alternatively, we can use the nest by function to nest this nest the data by cluster And then we can use the on nest function to recover the effect size level data Here's a function to run a selection model Inside the function we first fit an RMA-UNI meta regression model We then use the cell model function from metaphor to fit a selection model We don't need standard errors to be calculated in this step. So we're skipping those calculations here Which speaks things up We then compile parameter estimates as single vector Further, we use the possibly function from purr to handle errors By passing run cell model through possibly it will now spit out NA in case there are any convergence issues Or any errors when running the selection model Here is the completed fitting function called fit cell model First we take a subset of the data based on the index argument This generates a subset of the data based on re-sampled clusters We use the on nest function to get the effect size level data for those re-sampled clusters We then run the run cell model function here And we include the run cell model function inside the big function here to ease parallel processing The dot dot dot here refers to the contents of the run cell model function in the previous slide With our example Lehmann data set we create a nested data with one row per study And fit the selection model using fit cell model These are the point estimates from the three parameters selection model Now we can bootstrap using the boot function which takes in the nested data set And the function to fit the selection model Arguments for steps Number of bootstrap replications and any further options for parallel processing Parallel processing is really useful here because we get 2000 bootstraps in under one minute To get bootstrap conference intervals we can use the bootci function Specify the type of conference intervals and specify the index of the parameter that we want Here the index of one is for the overall average effect size And we get the conference intervals for the overall average effect Based on the selection model the overall average effect has gone down a bit From point two to point one three And the CI indicates that there's quite a bit of uncertainty around it Here we get the conference intervals for between study heterogeneity And for the selection rate So this has been a very quick demonstration of cluster bootstrapping for Selection cluster bootstrapping and selection model This cluster bootstrapping technique is interesting because we could in principle apply cluster Bootstrap to other models or methods to investigate selective reporting We are currently studying the performance of bootstrapping a three-parameter selection model And initial results suggest that the conference intervals like the one we showed you Have reasonable coverage Future directions include exploring other resampling methods such as fractional weight and bootstrap And turning the workflow that we presented here into a more user-friendly function Thank you so much for your attention And please feel free to reach out with any questions Thank you Thanks very much James and Mega Next we have Matt Lloyd-Jones who's going to be talking about a Proportionate response to comparing proportional outcomes in metronalysis Over to you Matt Hi my name is Matt Lloyd-Jones and today I'll be talking to you about some ways of dealing with Proportion data in metronalysis So what is proportion data? Well proportion data is simply data that is presented as parts of a whole So it could be proportions percentages or prevalences They're limited to 0 to 1 or 0 to 100 percent And some of the research questions you might have relating to proportion data are demonstrated here So my one was how does the proportion of resistant bacteria in the fecal microbiome Differ between antibiotic treated and untreated cattle How does proportion data typically manifest in the scientific literature? Well typically we don't have the raw data and we're limited by what studies present Typically studies only present proportion data in their figures Some studies won't even present that proportion data directly and they'll Present figures of the numerator and denominated data from which we have to calculate proportions And then alongside that a few studies after a long hard battle will provide raw data And what so we're left with these different levels of detail in terms of data that we have to combine into a metronalysis Okay, so with all that in mind I'm going to be taking you through three problems that I came across when dealing with proportion data in my meta-analysis And the proposed solutions that I implemented in the hope that they can help you I'm going to be highlighting the r packages and functions I used in blue on my slide So keep a pen handy for writing those down if you're trying to do something similar So perhaps the most obvious problem with proportion data is that they are restricted to a 0 to 1 or 0 to 100 Range which means they don't meet the assumptions of normality So given that proportion data do not immediately meet the assumptions of normality If we're going to use parametric tests for meta-analysis Then we need to do something to the data In order to deal with this and one common way of dealing with this is to transform the data To get it into a format which more closely approximates a normal distribution And there are many options for transformation Including log log it arc sign and double arc sign transformations And there's a lot of chatter about the relative merits of these different types and it's often confusing To the meta-analysis which type is the best to use in their case So which one did I use? Well, I used the arc sign transformation And I implemented this transformation using the transfer arc sign function of the metaphor package So the arc sign transformation has benefits over the log or log it transformation in terms of dealing with Sampling variances better and also over the double arc sign transformation in terms of back transformation and Interpretability to be fair the arc sign transformation has its own criticisms So one of the criticisms is around its interpretability. So if you use this in a conventional modeling context You can get predictions over or outside of the naught to one range But I argue that actually when you're using this in a meta-analysis context What you actually do is you generate effect sizes first which you then put into your models And so implicitly deals with this problem And actually if you go back to some of cohen's early work He provides even guidance on how to transfer all the effect sizes back into approximate differences in proportions between your control and treatment groups So I argue that that's less an issue in meta-analysis The other argument is that GLMMs accounting for binomial distribution are better Dealing with proportion data But this in a meta-analytical context is perhaps less relevant because as I Demonstrated earlier, you're often you don't have The underlying Numerator and denominator data. You just have proportions presented. So you can't even use these methods And there are other issues with these methods in terms of dealing And model fitting with sparse data Which we often have problems with in meta-analysis anyway So I think the arc's transformation is a good pragmatic choice in terms of dealing with proportion data So problem two is even before you've got to the question of how to deal with your proportion data in modeling You may not have your proportions directly presented in the paper That you're trying to incorporate into your meta-analysis So while some studies will only report proportions You'll come across other studies that don't report proportions at all And they actually just report the numerator and denominator variables that would make up that proportion And in these cases almost always you've only got some measure of the mean And variance of those proportions rather than individual data points And this makes calculating that a proportional mean of variance quite challenging So how do you calculate the mean of variance of the proportion based on this data alone? Well, the only way of dealing with this problem that I can see Is to simulate the underlying data based on those means and variances of the numerator and denominator that you do have And then to divide them by each other in order to estimate the mean and variance of the proportion And this is fairly easy to implement using base functions in R You can plug in your means and standard deviations of your numerator and denominator variables And and simulate vectors of simulated data And then what you can do with those is you divide one by the other to calculate a simulated vector of proportions And then from that you can calculate a simulated mean and variance of a proportion Of course, this is not ideal But then most things in match analysis are not and you're kind of bound to getting everything into this proportion format By the fact that many studies only report things in proportions as I mentioned earlier With this kind of thing I'd recommend a sensitivity analysis based on removing the simulated data Just to check that it's not having a disproportionate influence on your overall results And the final problem that I want to highlight is the lack of interpretability Of proportional differences in metric analysis So by their very nature proportions obscure what is happening in the underpinning numerator and denominator data So the proportion of your numerator can change either because it's absolute value changes Or because the proportion of the corresponding denominator changes So for example, the proportion of resistant bacteria in the population May increase because the resistant bacteria grow and increase in number Or alternatively the proportion may increase because the absolute value Of the denominator decreases and these obviously have very different implications in terms of Interpreting what's going on in our data And I actually think this is a bigger interpretability problem than some of those I mentioned earlier And the way I propose to deal with it is to use absolute count data where it is available alongside Your proportion data on which your main analysis is built So you have your effect sizes based on your proportion data which cover all of your studies and you've plotted and modeled those But I think you should also alongside those plot and model the absolute counts where they are available And this can give you a sense of whether what you're seeing is an actual increase In your numerator or associated with a change in the denominator So for example, if we plot effect sizes based on the Absolute number of resistant bacteria alongside those based on the proportions We can see if the resistant bacteria are growing and increasing in number Or it's just the fact that your susceptible bacteria are being wiped out and this can really aid the interpretation Of your meta analysis, which can be very abstract as we know So in summary, we often have to deal with outcomes reported as proportions whether we like it or not I proposed some potential pragmatic solutions for dealing With this data in the form in which we often encounter it when we're doing meta analysis But of course the real problem here is that people don't publish their data now allowing us to Fully make use of it and the real solution of course is for journals universities and funders to enforce and or reward data sharing So we can do more rich analysis So finally, I'd like to thank the whole evidence synthesis team that was involved Not just in the meta analysis, but the wider systematic review project In terms of the meta analysis, I'd like to thank Alfredo Sanchez Toha who was my Main meta analytics will collaborate. I'd also like to thank Shinichi Nakagawa who provided some useful email correspondence on the transformations part of this And Dan Padfield my colleague who came across similar problems outside of meta analysis and sort of influenced my thinking on this a bit Finally, here's a brief bibliography slide in case you want to follow up on any of the resources I presented. Thanks for listening Many thanks indeed. That was a really interesting talk So that closes off this session for today. That's it for quantitative synthesis part two We hope that you've enjoyed this session as always keep the questions coming in via twitter by following us at es hackathon And we'll try and get our presenters to answer those over the next few hours or days So do please keep those questions coming in. Enjoy the rest of the conference and see you again soon