## Upcoming Workshops, Spring 2023

**Introduction to Meta-analysis in Stata**, Monday, May 8 from 1 to 4 p.m. PDT via Zoom

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/tJYlceihrzMiGNG4cItOYbx-gb_vYPKCSnMj**

The workshop notes are here.

**R Graphics: Introduction to ggplot2**, Monday, May 15 from 1 to 4 p.m. PDT via Zoom

This workshop teaches the “grammar” of graphics that underlies the ggplot2 package, allowing the user to build eye-catching, publication-quality graphics layer-by-layer. We cover the basic elements of the grammar of graphics, including aesthetics, geoms, scales, and themes, and we will show you how easy ggplot2 makes it to integrate these elements to make informative and beautiful graphics. The seminar is meant to be interactive with attendees participating in the coding, so some very basic R coding knowledge is helpful but not required.

**Register here: https://ucla.zoom.us/meeting/register/tJYlcu6hrD8sH9dfPbYM6BKnOD9bvGJ539AN**

The workshop notes are here.

**Introduction to R Programming**, Monday, May 22 from 1 to 4 p.m. PDT via Zoom

This workshop is an introduction to R as a programming language. The aim of this workshop is to improve programming skills of R users who have some familiarity with R as a statistical package and would like to extend their R skills. We will talk about how R users can write functions to replace repetitive code and loops to iterate over the same algorithm repeatedly. Coding is essential in statistical computing and analysis, and as researchers sometimes we need to write our own computational code. We will also talk about some functional programming aspects of R so we can make our code more efficient.

#### Register here: https://ucla.zoom.us/meeting/register/tJcuc–qrjkvHtFWBYv9CKnINZiDL_HoSt63

The workshop notes will be posted soon.

## Past Classes and Workshops Available Online

- Introduction to Stata 16
- Stata Data Management
- Regression with Stata
- Logistic Regression with Stata
- Beyond Binary Logistic Regression with Stata
- Multiple Imputation in Stata 15
- Introduction to Survey Data Analysis
- Applied Survey Data Analysis
- Advanced Topics in Survey Data Analysis
- Survival Analysis Using Stata
- Introduction to Meta-analysis using Stata
- Introduction to Programming in Stata
- Decomposing, Probing, and Plotting Interactions in Stata

- Introduction to SAS 9.4
- Programming Basics in SAS 9.4
- Analyzing and Visualizing Interactions in SAS 9.4
- Regression with SAS
- Logistic Regression in SAS
- Repeated Measures Analysis in SAS
- Applied Survey Data Analysis using SAS 9.4
- Multiple Imputation in SAS 9.4
- Survival Analysis Using SAS
- Using Arrays in SAS
- Introduction to SAS Macro Language

- Introduction to SPSS (point-and-click and syntax)
- Introduction to Regression with SPSS
- Introduction to Mediation Models with the PROCESS macro in SPSS
- Graphing Interactions Using the PROCESS Macro in SPSS
- A Practical Introduction to Factor Analysis
- Principal Components (PCA) and Exploratory Factor Analysis (EFA) with SPSS
- Introduction to SPSS Syntax, Part1 (using SPSS version 21)
- Introduction to SPSS Syntax, Part 2 (using SPSS version 21)
- SPSS Syntax to the Next Level
- Repeated Measures Analysis in SPSS
- Using the SPSS Mixed Command
- Graphics using SPSS

**Mplus and Latent Variable Analysis**

- Introduction to R
- R Data Management
- R Markdown Basics
- Introduction to ggplot2
- Introduction to Regression in R
- Decomposing, Probing and Plotting Interactions in R
- Analysis and Visualization of Interactions in R
- Survey Data Analysis with R
- Introduction to Survival Analysis in R
- Repeated Measures Analysis in R
- Latent Growth Models (LGM) and Measurement Invariance with R in lavaan
- Introduction to Structural Equation Modeling (SEM) in R with lavaan
- Confirmatory Factor Analysis with in R with lavaan
- Missing Data in R
- Beyond Logistic regression in R

**Longitudinal Data Analysis**

- Longitudinal Research: Present Status and Future Prospects by Judith Singer & John Willett
- Analyzing Longitudinal Data using Multilevel Modeling

**Power Analysis**

- Deciphering Interactions in Logistic Regression
- Regression Models with Count Data
- Statistical Writing

**Other**