Meta-analysis is the synthesis of results from previous studies.  It is used to increase power, obtain a better estimate of an effect size, and sometimes to resolve conflicting conclusions in the literature.  In this workshop, we will discuss how the data for a meta-analysis are collected and organized, as well as how such data are analyzed and graphed.  We will also discuss some of the limitations meta-analysis and what should be included in a meta-analysis for publication. Register here:  https://ucla.zoom.us/meeting/register/tJUpcO-vpzsqH93pnL7-ZfVKhYwxcbaX6j5f…

The purpose of this workshop is to discuss techniques and introduce some useful packages in R for handling missing data. In particular, we will focus on multiple imputation and how to perform it using the R package, mice: “Multivariate Imputation by Chained Equations”.  As prerequisite to this seminar, we suggest participants have basic knowledge in R and if they do not have prior training in R, a seminar providing an introduction R can be found here: https://stats.idre.ucla.edu/r/seminars/intro/. Register here:  https://ucla.zoom.us/meeting/register/tJMod-urpjwsGt0IpKni-92vrKDJsIyKclhO…

In regression, we are often interested in an interaction, which is the modification or moderation of the effect of an independent variable by another.  Understanding interactions involves interpreting the regression coefficients, estimating and testing simple effects and their differences, and visualizing the interaction.  This workshop will teach you how to do all of these thing in R using base R, as well as the emmeans and ggplot2 packages.  Some prior knowledge of linear regression and experience with R is recommended…