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.
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.
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.
In this blog post, I use Gelman and Loken’s garden of forking paths analysis to construct a simulation showing why skepticism of AstraZeneca’s vaccine results is warranted at this early stage.
I start with Eric Novik’s excellent blog post on how to calculate the relevant statistics for the vaccine, i.e. vaccine efficacy (VE). This is defined as:
\[ VE = 1 - \frac{p_t}{p_c} \]
My wife and I have been faced with a decision in our pregnancies that has always caused me some consternation: should we take the MaterniT 21 test to see if our baby might have Down’s syndrome (trisomy 21) or other genetic abnormalities?
We’ve all been in that seminar where the author puts up a slide containing regression coefficients, and buried in the bottom line of the table we can see little Ys and Ns indicating the kind of panel data model employed.