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including fixed effects in gls estimation glm models with fixed effects are challenging to estimate and many glm models with fixed effects can't even be estimated consistently conditional logistic recursive model is one workaround to the problem that fixed effects in a logistic regression simply can't be estimated these kind of models are often used in for example ceo selection studies and sometimes in panel data sets where the dependent variable is binary let's take a look at first what is the problem that conditional fixed effects logistic recursion addresses or what does the conditional in the estimation mean when we talk about linear models then we have two commonly used panel data analysis techniques to deal with unoptional heterogeneity we have uh the fixed effects model where we model these consistent differences between the the groups or the clusters using uh this fixed effect that we estimate separately for each cluster this is known as the dummy variable model because the si...
