## Upcoming Workshops, Summer 2024

**R Markdown Basics**, Monday, August 5 from 1 to 4 p.m. PDT via Zoom

R Markdown files integrate text, Markdown, and R code into dynamic documents that weave together plain text, formatted text, and the output of the R code. The resulting dynamic reports can be produced in many formats, including HTML documents, HTML slideshows, LaTeX pdf, Beamer slideshows, MS Word doc, books, scientific articles, and websites. This seminar covers basic coding and conventions of the 3 frameworks upon which R Markdown depends: Markdown for formatting text, knitr for R code chunks, and YAML for rendering the document. The seminar does not assume any previous experience with R Markdown, but attendees who wish to participate in seminar demonstrations should come with RStudio and R Markdown installed on their computers.

The workshop notes are here .

**Register here: https://ucla.zoom.us/meeting/register/tJcrdeChpz4oHNKqGdwj7PzJ2iusMhvMZkGt
**

**Applied Survey Data Analysis in Stata**, Monday, August 12 from 1 to 4 p.m. PDT via Zoom

This workshop will cover both the use of descriptive and inferential statistics with complex survey data in Stata. We will also discuss post-estimation commands, the analysis of subpopulations, and some graphical methods that can be used with weighted data.

The workshop notes are here .

**Register here: https://ucla.zoom.us/meeting/register/tJYscumupjIiHdT9wcNaub47AFm_iz1E5_ip
**

**Output Tables in R**, Monday, August 19 from 1 to 4 p.m. PDT via Zoom
R is a powerful programming language specifically designed for statistical analysis. In this workshop, we will explore some of the tools and packages available in R to craft visually appealing tables that effectively communicate your results. Whether you’re using R Markdown and seeking to generate tables in your HTML file or aiming to create polished and publication-ready tables in your report, these packages can greatly enhance the clarity of your work.

The workshop notes will be posted soon.

**Register here: https://ucla.zoom.us/meeting/register/tJcvd-iqpj8iEtVFYODj4APCKZi3Dme0pMAA**

## Past Classes and Workshops Available Online

- Introduction to Stata 16
- Introduction to Stata 18
- 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 using SAS OnDemand (new)
- 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
- Applied Survey Data Analysis Using SPSS 29
- Repeated Measures Analysis in SPSS
- Using the SPSS Mixed Command
- Graphics using SPSS

**Mplus and Latent Variable Analysis**

- Introduction to Mplus
- Building Your Mplus Skills
- A Practical Introduction to Factor Analysis
- Introduction to Mediation Analysis using Mplus

- Introduction to R
- R Data Management
- R Markdown Basics
- Introduction to ggplot2
- Introduction to Linear Regression in R
- 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
- Introduction to R Programming
- Introduction to Generalized Linear Regression Model in R
- Beyond Logistic regression in R
- Zero-inflated and Hurdle models for Count Data 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**