This week a student asked me (quite reasonably) whether using linear regression to model binary outcomes was really such a bad idea, and if it was, why. In this post I’ll look at some of the issues involved and try to answer the question.
Jonathan Bartlett
Interpreting odds and odds ratios
Odds and odds ratios are an important measure of the absolute/relative chance of an event of interest happening, but their interpretation is sometimes a little tricky to master. In this short post, I’ll describe these concepts in a (hopefully) clear way.
Missing covariates in structural equation models
This week I was talking to a friend about how covariates which have missing values are handled in structural equation modelling (SEM) software. I’ll preface this post by saying that I’m definitely not an expert (or anywhere close!) in structural equation models, so if anyone spots errors/problems please add a comment. My friend thought that certain implementations of SEMs in some packages have the ability to automatically accommodate missingness in covariates, using so called ‘full information maximum likelihood’. In the following I’ll describe my subsequent exploration of how Stata’s sem command handles missingness in covariates.