In 2019, Rights and Sterba introduced a set of effect size measures for linear multilevel models in the article Quantifying Explained Variance in Multilevel Models: An Integrative Framework for Defining R-Squared Measures. This workshop discusses the concepts of within-cluster and between-cluster variance in multilevel models, and how these new R-squared measures quantify how the components...
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Survival analysis models time-to-event outcomes. This workshop introduces usage of the survival package in R for some of the most commonly used survival methods. Topics include data setup, Kaplan-Meier estimates and curves, log-rank tests, fitting the Cox proportional hazards model, assessing the proportional hazards assumption, and modeling time-varying covariates. Experience in both survival analysis and...
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This workshop will introduce mediation (i.e., causal) models using Mplus. Explanations of the syntax and output will be given, as well as some tips about reporting such analyses. Models with latent variables will not be discussed. The workshop notes are here:  https://stats.oarc.ucla.edu/mplus/seminars/introduction-to-mediation-analysis-using-mplus/ Register here:  https://ucla.zoom.us/meeting/register/tJUpd-GppzwoH9S11q9Ckgr1oo8yOT-bWdJk

This workshop teaches the basics of the linear regression model, the foundation for most other regression models. Topics include understanding the model equation, continuous and categorical predictors, interpreting the model estimates, and diagnostics for assessing model assumptions. The workshop is intended to be interactive, with examples and exercises in R, and assumes only introductory exposure...
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In this workshop we discuss generalized linear models and why and when we need to use them. We will discuss several generalized linear modes such as logistic, Poisson, and negative binomial and how we run them in R. The seminar briefly reviews regression concepts as necessary, but it is assumed that participants have basic understanding...
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