TL;DR: When you have longitudinal data, you should use fixed effects or ANCOVA rather than difference-in-differences since a difference-in-difference specification will spit out incorrect variance estimates. If the data is from a randomized trial, ANCOVA is probably a better bet. Trying to understand when to use fixed effects and when to use difference-in-differences (DiD), in the past, always made me feel like an idiot. It seemed like I was missing something really obvious that everyone else was getting. Read more

layout: post title: “Multiple Hypothesis Testing” date: 2016-07-04 10:40:48 -0400 categories: jekyll update This week, I volunteered to read and summarize one of the articles for IDinsigh’s tech team’s book club. The topic for this week is multiple hypothesis testing and the article I volunteered to summarize is “Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects” by Michael Anderson. Read more