Is Dummy Variable Adjustment Ever Good for Missing Data?
For many years, one of the more popular ways of handling missing data was a technique known as dummy variable adjustment...
Sep 27, 2022
When Do Suppressor Effects Occur?
When doing regression analysis, most data analysts expect that the coefficient associated with a predictor variable will get smaller (closer to...
Aug 30, 2022
Is OLS BLUE or BUE?
If you’ve ever taken a course on linear regression, you probably learned that ordinary least squares (OLS) is BLUE—the best linear...
Jul 12, 2022
Making Your First GitHub R Project
Increasingly, academic scholars, data scientists, and quantitative researchers are turning to GitHub for collaboration and to share data, code, and results. GitHub allows...
Aug 12, 2021
An Update on The MatchIt Package in R
One of the things we hope to do at Code Horizons is help steer you toward the best tools to meet...
Dec 08, 2020
Better Predicted Probabilities from Linear Probability Models
In two earlier posts on this blog (here and here), my colleague Paul von Hippel made a strong case for using...
Apr 24, 2020
Introducing Code Horizons
We are thrilled to introduce a new addition to the Statistical Horizons family — Code Horizons. This new initiative emerges from...
Jan 24, 2020
How many imputations do you need?
When using multiple imputation, you may wonder how many imputations you need. A simple answer is that more imputations are better....
Oct 30, 2019
R Should Be Your Second Language (If It’s Not Already Your First)
When R first came out, around the year 2000, I was really excited. Here was a powerful, programmable statistical package that...
Apr 19, 2019
Asymmetric Fixed Effects Models for Panel Data
Standard methods for the analysis of panel data depend on an assumption of directional symmetry that most researchers don’t even think...
Oct 12, 2018
Instrumental Variables in Structural Equation Models
When I teach courses on structural equation modeling (SEM), I tell my students that any model with instrumental variables can be...
Jun 26, 2018
For Causal Analysis of Competing Risks, Don’t Use Fine & Gray’s Subdistribution Method
Competing risks are common in the analysis of event time data. The classic example is death, with distinctions among different kinds...
Mar 24, 2018