Description
This course introduces multilevel/mixed modeling for nested and longitudinal data and its implementation in Stata. Mixed models contain both fixed effects, analogous to regression coefficients, and random effects, effects that vary across clusters. Participants will learn how to use mixed models to answer research questions about the observation- and cluster-level data and how to disaggregate these effects. Introductory theory, estimation, model building, and diagnostics will be discussed and demonstrated through many examples.
Are you more interested in panel-data models with unobserved individual-level heterogeneity, endogenous variables, or lagged variables? Check out our Panel-data analysis using Stata course.
The course will be interactive, use real data, and offer ample opportunity for specific research questions and for working exercises to reinforce what is learned.
Course topics
Prerequisite
Basic knowledge of standard linear regression and a working knowledge of Stata.
Notes
This course is available in-person or virtually. In-person training courses generally run for eight hours per day and include morning and afternoon breaks and a lunch break. Virtual training courses are typically divided into three- to four-hour daily sessions. You can arrange a convenient schedule with your instructor.
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Teaching with Stata
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