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Distinguished Speaker Series: A Seminar taught by Andrew F. Hayes
“PROCESS vs. Structural Equation Modeling: The Analysis of the Mechanisms and Contingencies of Effects”

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What Are Models and Why Should We Use Them to Understand Social Behavior?

As scientists, we try to increase our understanding of the world through research. We study objects and systems to learn about their properties and behaviors. Or do we?
Paul Smaldino December 6, 2023

In Defense of Logit – Part 2

In my last post, I explained several reasons why I prefer logistic regression over a linear probability model estimated by ordinary...
Apr 27, 2017

In Defense of Logit – Part 1

In a recent guest blog, Paul von Hippel extended his earlier argument that there are many situations in which a linear...
Mar 28, 2017
4

When Can You Fit a Linear Probability Model? More Often Than You Think

In July 2015 I pointed out some advantages of the linear probability model over the logistic model. The linear model is...
Mar 08, 2017
1

Causal Mediation Analysis

On April 21-22, 2017, I will be offering a seminar on causal mediation analysis in Philadelphia with Statistical Horizons. The course...
Mar 06, 2017

Teaching Stata in Bangladesh

When Paul Allison asked me if I wanted to teach a course in Bangladesh, my first reaction was confusion.  Other than...
Sep 18, 2015
1

Linear vs. Logistic Probability Models: Which is Better, and When?

In his April 1 post, Paul Allison pointed out several attractive properties of the logistic regression model.  But he neglected to consider...
Jul 05, 2015
23

Don’t Put Lagged Dependent Variables in Mixed Models

When estimating regression models for longitudinal panel data, many researchers include a lagged value of the dependent variable as a predictor....
Jun 02, 2015
96

Maximum Likelihood is Better than Multiple Imputation: Part II

In my July 2012 post, I argued that maximum likelihood (ML) has several advantages over multiple imputation (MI) for handling missing data:...
May 05, 2015
8

What’s So Special About Logit?

For the analysis of binary data, logistic regression dominates all other methods in both the social and biomedical sciences. It wasn’t...
Apr 01, 2015
14

Imputation by Predictive Mean Matching: Promise & Peril

Predictive mean matching (PMM) is an attractive way to do multiple imputation for missing data, especially for imputing quantitative variables that...
Mar 05, 2015
24

Getting the Lags Right

In my November and December posts, I extolled the virtues of SEM for estimating dynamic panel models. By combining fixed effects...
Feb 10, 2015
5

More on Causal Inference With Panel Data

This is a follow-up to last month’s post, in which I considered the use of panel data to answer questions about...
Nov 25, 2014