Longitudinal Data Analysis Using Stata – January 2023

Event Phone: 1-610-715-0115

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A 3-Day Livestream Seminar Taught by Stephen Vaisey, Ph.D.

The most common type of longitudinal data is panel data or repeated measures data, consisting of measurements of predictor and response variables at two or more points in time for many individuals (or other units). Panel data enable two major advances over cross-sectional data:

  1. the ability to model the evolution of outcomes over time; and
  2. the ability to “control” for unobserved unit-specific heterogeneity, enabling better causal inferences.

Different data structures allow researchers to use panel data in different ways. In this course, we will focus on the following approaches:

  1. Mixed models (including latent growth curves)
  2. Two period difference-in-differences
  3. Fixed-effects models (one-way and two-way)
  4. Between-within models
  5. Dynamic panel models

In addition to considering these approaches and their implementation in Stata, we will discuss when each is (not) suitable given data constraints. We will also consider how to adapt these approaches to deal with limited dependent variables (especially binary outcomes).

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