This post focuses on one of the more curious models in contemporary statistics, a specification for proportions that is either called fractional logit or quasi-Binomial. While in most cases in statistics, the evaluation of a model necessarily involves trade-offs in which a model is best applied to certain cases but not others, in this case fractional logit is simply the wrong model.
I am writing this post in response to questions about estimating turnout for Tunisia’s constitutional referendum today. Turnout is an important aspect to this referendum because high turnout would signal higher legitimacy for President Kais Saied’s dramatic changes to the Tunisia’s democracy.
Introduction Limited dependent variables, or continuous variables with lower and upper bounds, are quite common in the social sciences but do not fit easily with existing statistical models. In this Rmarkdown document, I show why these issues are important to consider when modeling your data, discuss existing R packages useful for fitting these models, and also present ordbetareg, an R package with a new variant of Beta regression that builds on and simplifies existing approaches (see paper here that is forthcoming in Political Analysis).
NB: An earlier version of this post critiqued Victor Chernozhukov’s approach to directed a-cyclic graphs and fixed effects, but made some critical errors in interpreting his approach. These errors were entirely mine, and I apologize to Victor for doing so.
There has been plenty of discussion about declining fertility rates and patterns of marriage among people in the United States following the news that the US birth rate declined to its lowest since the Great Depression.
The COVID-19 pandemic has led to a wealth of research studies examining various aspects of the pandemic. In this post, I will discuss some of the available datasets for doing aggregate level analysis, i.
While perusing the news, I read eagerly about the CDC’s recent study examining associations between county-level mask mandates and COVID-19 growth rates. This study has already been the subject of angry retorts from the restaurant industry due to the CDC’s claim that restaurant closures reduced COVID-19 spread.