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Solving for Hidden Data

Introduction Let’s continue along the lines discussed in Omitted Variable Effects in Logistic Regression. The issue is as follows. For logistic regression, omitted variables cause parameter estimation bias. This is true even for independent variables, which is not the case for more familiar linear regression. This is a known problem […]

Omitted Variable Effects in Logistic Regression

Introduction I would like to illustrate a way which omitted variables interfere in logistic regression inference (or coefficient estimation). These effects are different than what is seen in linear regression, and possibly different than some expectations or intuitions. Our Example Data Let’s start with a data example in R. # […]

Frequentist inference only seems easy

Two of the most common methods of statistical inference are frequentism and Bayesianism (see Bayesian and Frequentist Approaches: Ask the Right Question for some good discussion). In both cases we are attempting to perform reliable inference of unknown quantities from related observations. And in both cases inference is made possible […]