Upcoming Workshops, Winter 2025
Introduction to Survival Analysis in R, Monday, February 10 from 1 to 4 p.m. PT via Zoom
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 R will be helpful but not necessarily required to follow the workshop material.
The workshop notes are here: https://stats.oarc.ucla.edu/r/seminars/introduction-to-survival-analysis-in-r/
Register here: https://ucla.zoom.us/meeting/register/tJ0scuCspz4sHNyKIWewpu58WQ2-uFLfk4lL
Introduction to Mediation Models using Mplus, Monday, February 24, 2025 from 1 to 4 p.m. PT 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 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
Introduction to Linear Regression in R, Monday, March 3, 2025 from 1 to 4 p.m. PT 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/tJYvd-6vrzkqHdc9wxMdchhMXz1ISwLcrhZo#/registration
Generalized Linear Regression Models in R, Monday, March 10, 2025 from 1 to 4 p.m. PT via Zoom
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 of linear regression models (see the Introduction to Regression in R workshop). It also assumed that participants have basic familiarity with R (see the Introduction to R seminar for a tutorial).
The workshop notes are here: https://stats.oarc.ucla.edu/r/seminars/generalized_linear_regression/
Register here: https://ucla.zoom.us/meeting/register/tJwlceygqjouHd1Dwscdeg_NHKbuf1N-Aq0g
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, using SPSS version 29)
- 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
- Output Tables in R
- Effect Size Measures for Linear Multilevel Models 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