Panel Data Regression

A panel data set contains observations collected from randomly selected subjects from a large population and recorded over a fixed time frame. Panel data is a type of longitudinal data resulting from an observational study.

The main goal of a panel data regression analysis is to study the impacts predictor variables on a response variable, while controlling for heterogeneity, which is a latent, linear, subject-specific effect. A one-way random effects panel regression model treats the heterogeneity as uncorrelated with the predictor variables, while a one-way fixed effects model treats the heterogeneity as correlated with at least one predictor. This treatment contrasts with the linear mixed effect model treatment of effects for an analysis of experimental data. An additional goal, which distinguishes panel data analysis from a typical linear mixed effects model analysis, is to estimate the latent effects.