Designing Studies Introduction

Designing Studies

Now that we have learned about the first stage of data production— sampling—we can move on to the next stage—designing studies.

If haven’t read about it read from here.


Obviously, sampling is not done for its own sake. After this first stage in the data production process is completed, we come to the second stage, that of gaining information about the variables of interest from the sampled individuals. In this module we’ll discuss three study designs; each design enables you to determine the values of the variables in a different way. You can:

– Carry out an observational study, in which values of the variable or variables of interest are recorded as they naturally occur. There is no interference by the researchers who conduct the study.

– Take a sample survey, which is a particular type of observational study in which individuals report variables’ values themselves, frequently by giving their opinions.

– Perform an experiment. Instead of assessing the values of the variables as they naturally occur, the researchers interfere, and they are the ones who assign the values of the explanatory variable to the individuals. The researchers “take control” of the values of the explanatory variable because they want to see how changes in the value of the explanatory variable affect the response variable. (Note: By nature, any experiment involves at least two variables.)

The type of design used, and the details of the design, are crucial, since they will determine what kind of conclusions we may draw from the results. In particular, when studying relationships in the Exploratory Data Analysis unit, we stressed that an association between two variables does not guarantee that a causal relationship exists. In this module, we will explore how the details of a study design play a crucial role in determining our ability to establish evidence of causation.

Here is how this section is organized:

We’ll start this section by learning how to identify study types. In particular, we will highlight the distinction between observational studies and experiments.

We will then discuss each of the three study designs mentioned above.

  • We’ll discuss observational studies, focusing on why it is difficult to establish causation in these type of studies, as well as other possible flaws.
  • We’ll then focus on experiments, learning, among other things, that when appropriately designed, experiments can provide evidence of causation.
  • We’ll end the module by discussing surveys and sample size.

Types of Studies

Identifying Study Design

Because each type of study design has its own advantages and trouble spots, it is important to begin by determining what type of study we are dealing with. The following example helps to illustrate how we can distinguish among the three basic types of design mentioned in the introduction—observational studies, sample surveys, and experiments.

Suppose researchers want to determine whether people tend to snack more while they watch television. In other words, the researchers would like to explore the relationship between the explanatory variable “TV” (a categorical variable that takes the values “on'” and “not on”) and the response variable “snack consumption.”

Identify each of the following designs as being an observational study, a sample survey, or an experiment.

1. Recruit participants for a study. While they are presumably waiting to be interviewed, half of the individuals sit in a waiting room with snacks available and a TV on. The other half sit in a waiting room with snacks available and no TV, just magazines. Researchers determine whether people consume more snacks in the TV setting.

This is an experiment, because the researchers take control of the explanatory variable of interest (TV on or not) by assigning each individual to either watch TV or not, and determine the effect that has on the response variable of interest (snack consumption).

2. Recruit participants for a study. Give them journals to record hour by hour their activities the following day, including when they watch TV and when they consume snacks. Determine if snack consumption is higher during TV times.

This is an observational study, because the participants themselves determine whether or not to watch TV. There is no attempt on the researchers’ part to interfere.

3. Recruit participants for a study. Ask them to recall, for each hour of the previous day, whether they were watching TV, and what snacks they consumed each hour. Determine whether snack consumption was higher during the TV times.

This is also an observational study; again, it was the participants themselves who decided whether or not to watch TV. Do you see the difference between 2 and 3? See the comment below.

4. Poll a sample of individuals with the following question: While watching TV, do you tend to snack: (a) less than usual; (b) more than usual; or (c) the same amount as usual?

This is a sample survey, because the individuals self-assess the relationship between TV watching and snacking.


Notice that in Example 2, the values of the variables of interest (TV watching and snack consumption) are recorded forward in time. Such observational studies are called prospective. In contrast, in Example 3, the values of the variables of interest are recorded backward in time. This is called a retrospective observational study. We’ll discuss this distinction later.

Experiments vs. Observational Studies

1. An observational study of the relationship between these two variables requires us to collect a representative sample from the population of smokers who are beginning to try to quit. We can imagine that a substantial proportion of that population is trying one of the four above methods. In order to obtain a representative sample, we might use a nationwide telephone survey to identify 1,000 smokers who are just beginning to quit smoking. We record which of the four methods the smokers use. One year later, we contact the same 1,000 individuals and determine whether they succeeded.

2. In an experiment, we again collect a representative sample from the population of smokers who are just now trying to quit, using a nationwide telephone survey of 1,000 individuals. This time, however, we divide the sample into 4 groups of 250 and assign each group to use one of the four methods to quit. One year later, we contact the same 1,000 individuals and determine whose attempts succeeded while using our designated method.

The following figures illustrate the two study designs:

1. Observational study:

A visual representation of the Observational Study. A large circle represents the entire population. Through random selection we generate the sample, which is represented as a smaller circle. The circle representing the samples is divided up unevenly into 4 pieces, each piece representing one value of the explanatory variable (method), which have been "Self- Assigned" by the people in the sample.

2. Experiment:

A visual representation of the Experimental Study. A large circle represents the entire population. Through random selection we generate the sample, which is represented as a smaller circle. The circle representing the samples is divided up evenly into 4 pieces, each piece representing one value of the explanatory variable (method), which have been assigned by the researchers.

 Design Issues

Sample Surveys

A sample survey is a particular type of observational study in which individuals report variables’ values themselves, frequently by giving their opinions. Researchers have several options to choose from when deciding how to survey the individuals involved: in person, or via telephone, Internet, or mail.

The following issues in the design of sample surveys will be discussed:

  • open vs. closed questions
  • unbalanced response options
  • leading questions
  • planting ideas with questions
  • complicated questions
  • sensitive questions

These issues are best illustrated with a variety of concrete examples.

Suppose you want to determine the musical preferences of all students at your university, based on a sample of students. In the Sampling section, we discussed various ways to obtain the sample, such as taking a simple random sample from all students at the university, then contacting the chosen subjects via email to request their responses and following up with a second email to those who did not respond the first time. This method would ensure a sample that is fairly representative of the entire population of students at the university, and avoids the bias that might result from a flawed designs such as a convenience sample or a volunteer sample.

However, even if we managed to select a representative sample for a survey, we are not yet home free: we must still compose the survey question itself so that the information we gather from the sampled students correctly represents what is true about their musical preferences. Let us consider some possibilities:

Question: “What is your favorite kind of music?”

This is what we call an open question, which allows for almost unlimited responses. It may be difficult to make sense of all the possible categories and subcategories of music that survey respondents could come up with. Some may be more general than what you had in mind (“I like modern music the best”) and others too specific (“I like Japanese alternative electronic rock by Cornelius”). Responses are much easier to handle if they come from a closed question:

Question: Which of these types of music do you prefer: classical, rock, pop, or hip-hop?

What will happen if a respondent is asked the question as worded above, and he or she actually prefers jazz or folk music or gospel? He or she may pick a second-favorite from the options presented, or try to pencil in the real preference, or may just not respond at all. Whatever the outcome, it is likely that overall, the responses to the question posed in this way will not give us very accurate information about general music preferences. If a closed question is used, then great care should be taken to include all the reasonable options that are possible, including “not sure.” Also, in case an option was overlooked, “other:___________” should be included for the sake of thoroughness.

Many surveys ask respondents to assign a rating to a variable, such as in the following:

Question: How do you feel about classical music? Circle one of these: I love it, I like it very much, I like it, I don’t like it, I hate it.

Notice that the options provided are rather “top-heavy,” with three favorable options vs. two unfavorable. If someone feels somewhat neutral, they may opt for the middle choice, “I like it,” and a summary of the survey’s results would distort the respondents’ true opinions.

Some survey questions are either deliberately or unintentionally biased towards certain responses:

Question: “Do you agree that classical music is the best type of music, because it has survived for centuries and is not only enjoyable, but also intellectually rewarding? (Answer yes or no.)”

This sort of wording puts ideas in people’s heads, urging them to report a particular opinion. One way to test for bias in a survey question is to ask yourself, “Just from reading the question, would a respondent have a good idea of what response the surveyor is hoping to elicit?” If the answer is yes, then the question should have been worded more neutrally.

Sometimes, survey questions are ordered in such a way as to deliberately bias the responses by planting an idea in an earlier question that will sway people’s thoughts in a later question.

Question: In the year 2002, there was much controversy over the fact that the Augusta National Golf Club, which hosts the Masters Golf Tournament each year, does not accept women as members. Defenders of the club created a survey that included the following statements. Respondents were supposed to indicate whether they agreed or disagreed with each statement:

“The First Amendment of the U.S. Constitution applies to everyone regardless of gender, race, religion, age, profession, or point of view.”

“The First Amendment protects the right of individuals to create a private organization consisting of a specific group of people based on age, gender, race, ethnicity, or interest.”

“The First Amendment protects the right of organizations like the Boy Scouts, the Girls Scouts, and the National Association for the Advancement of Colored People to exist.”

“Individuals have a right to join a private group, club, or organization that consists of people who share the same interests and personal backgrounds as they do if they so desire.”

“Private organizations that are not funded by the government should be allowed to decide who becomes a member and who does not become a member on their own, without being forced to take input from other outside people or organizations.”

Notice how the first and second statements steer people to favor the opinion that specialized groups may form private clubs. The third statement reminds people of organizations that are formed by groups on the basis of gender and race, setting the stage for them to agree with the fourth statement, which supports people’s rights to join any private club. This in turn leads into the fifth statement, which focuses on a private organization’s right to decide on its membership. As a group, the questions attempt to relentlessly steer a respondent towards ultimately agreeing with the club’s right to exclude women.

Sometimes surveyors attempt to get feedback on more than one issue at a time.

Question: “Do you agree or disagree with this statement: ‘I don’t go out of my way to listen to modern music unless there are elements of jazz, or else lyrics that are clear and make sense.'”

Put yourself in the place of people who enjoy jazz and straightforward lyrics, but don’t have an issue with music being “too modern,” per se. The logic of the question (or lack thereof) may escape the respondents, and they would be too confused to supply an answer that correctly conveys their opinion. Clearly, simple questions are much better than complicated ones; rather than try to gauge opinions on several issues at once, complex survey questions like this should be broken down into shorter, more concise ones.

Depending on the topic, we cannot always assume that survey respondents will answer honestly.

Question1: “Have you eaten rutabagas in the past year?”

If respondents answer no, then we have good reason to believe that they did not eat rutabagas in the past year.

Question2: “Have you used illegal drugs in the past year?”

If respondents answer no, then it is still a possibility that they did use illegal drugs, but didn’t want to admit it.

Effective techniques for collecting accurate data on sensitive questions are a main area of inquiry in statistics. One simple method is randomized response, which allows individuals in the sample to answer anonymously, while the researcher still gains information about the population.

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