Marginal effects of logit in weighted survey data using R
<p>I´m trying to estimate marginal effect of a logit model in which I have several dichotomous explanatory variables. </p>

<p>Let's say the model estimated by</p>

<pre><code>logit&lt;- svyglm ( if_member ~ if_female + dummy_agegroup_2 + dummy_agegroup_3 + dummy_education_2 + dummy_education_3 + dummy_education_4, family = quasibinomial(link = "logit"), design = survey_design)
</code></pre>

<p>I know about the <strong>marginpred</strong> function in survey package, but I am not very familiar with it. I have only dichotomous variebles in the model so I am wondering how to estimate marginal effects by this function, especially I am not sure about the <strong><em>predictat</em></strong> (A data frame giving values of the variables in model to predict at).</p>