Perhaps no other subject in applied statistics and machine learning has caused people as much trouble as the humble logit model. Most people who learn either subject start off with some form of linear regression, and having grasped it, are then told that if they have a variable with only two values, none of the rules apply.
Robustness check: time of completion Survey Design Sensitivity Estimates Alternative Estimation: RRreg Alternative Estimator: rr BRMS Model Adjustment with MRP Gender Age Region Simulation Comparison: Univariate Vs.
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. An earlier version of this blog post had a much more negative take on the fractional logit specification.
Twitter (or what’s left of it) was recently ablaze with a discussion of two smart working papers, one by Jiafeng Chen and Jonathan Roth and the other by John Mullahy and Edward Norton.
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.
Interested in more social science on contemporary issues? Check out my just-released book with Cambridge University Press and use discount code KUBINEC23 to get 20% off.
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.
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.
Interested in more social science on contemporary issues? Check out my just-released book with Cambridge University Press and use discount code KUBINEC23 to get 20% off.
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.
This tutorial gives an overview of the COVID-19 policy indexes just released by the CoronaNet project of which I am a part and the Oxford Government Response Tracker.