Introduction to Regression Models for Panel Data Analysis

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dc.contributor.authorMcManus, Patricia
dc.date.accessioned2025-01-23T14:58:28Z
dc.date.available2025-01-23T14:58:28Z
dc.date.issued2025-01-24
dc.descriptionPatricia McManus is a professor of Sociology at Indiana University. Her research agenda addresses social mobility, family transitions and material well-being in the U.S. and Europe.
dc.description.abstractThis workshop provides an introduction to the analysis of panel data (sometimes called cross-section time-series data) using Stata statistical software. The focus is on the linear error components model. We cover what differentiates panel data from other longitudinal data, why use panel analysis techniques and how to use Stata’s “xt” suite of commands to facilitate data exploration and analysis. The workshop introduces linear fixed effects models (in three flavors), random effects models, and Allison’s (2009) hybrid model. Participants may have the opportunity to follow along using a small example dataset.
dc.identifier.urihttps://hdl.handle.net/2022/33345
dc.language.isoen_US
dc.publisherIndiana University Workshop in Methods
dc.rightsThis work may be protected by copyright unless otherwise stated.
dc.titleIntroduction to Regression Models for Panel Data Analysis
dc.typePresentation

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