## Upcoming Workshops, Winter 2024

**Introduction to Linear Regression in R**, Monday, February 26 from 1 to 4 p.m. PDT via Zoom

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 to R.

The workshop notes are here: https://stats.oarc.ucla.edu/r/seminars/intro-to-linear-regression-r/ .

**Register here: https://ucla.zoom.us/meeting/register/tJMqfuytqj8oG9alsqSni4ikfXAeBaAMKsaK
**

**Zero-inflated and Hurdle models for Count Data in R**, Monday, March 4 from 1 to 4 p.m. PDT via Zoom
This workshop introduces zero-inflated Poisson, zero-inflated negative binomial, and hurdle models for count data, which are two-part models used when more zeros are found in the data than expected with typical count distributions. We will discuss the formulations of the two parts of each model, the interpretation of model parameters, and how to run these models and analyze zero-inflated count data in R.

The workshop notes will be posted soon.

**Register here: https://ucla.zoom.us/meeting/register/tJ0lcu2rpz8iGtS9aC08h0VWbmCzDUev_HCG
**
**Introduction to Mediation Models in Mplus**, Monday, March 11 from 1 to 4 p.m. PDT via Zoom

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 will be posted soon.

**Register here: https://ucla.zoom.us/meeting/register/tJcocOmopjotGNBLZEvBOgjen-6vIcMCqm-3
**

## 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
- 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 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
- 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**