## Workshops for Spring, 2021

**R Graphics: Introduction to ggplot2, Monday, May 3 from 1 to 4 p.m. PDT**

Zoom registration required: https://ucla.zoom.us/meeting/register/tJAucO-orzkvHtGtJFXfN76vvx75TY-1QxIG

This seminar 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.

All researchers are welcome to register for this free workshop; affiliation with UCLA is not required.

**Introduction to Regression in R, Monday, May 10 from 1 to 4 p.m. PDT**

Zoom registration required: https://ucla.zoom.us/meeting/register/tJAocumvrTkoHdVjqIGxWTdErUZLo_Z5hccE

Regression analysis is one of the most powerful statistical techniques that is used to explain variability in a response (dependent) variable as a function of one or more predictor (explanatory or independent) variables. The aim of this seminar is to help participants increase their skills in using regression analysis with R. The seminar begins with simple regression and generalizes the methods to multiple regression, followed by regression diagnostics. The seminar briefly reviews regression concepts as necessary, but it is assumed that participants have had at least a one quarter/semester course in introduction to statistics and also basic familiarity with R (see the Introduction to R seminar for a tutorial).

All researchers are welcome to register for this free workshop; affiliation with UCLA is not required.

**Confirmatory Factor Analysis (CFA) in R with lavaan, Monday, May 17 from 1 to 4 p.m. PDT**

Zoom registration required: https://ucla.zoom.us/meeting/register/tJwkcuiqrjovGdFdq0u6EebmpiiX_KW00ohH

This workshop will cover basic concepts of confirmatory factor analysis by introducing the CFA model and looking at examples of a one-factor, two-factor and second-order CFA. Concepts such as model identification, standardized solutions, and model fit statistics such as the chi-square statistic, CFI, TLI and RMSEA will be covered. The focus is on learning the CFA model and how to implement and interpret the output in R’s lavaan package.

All researchers are welcome to register for this free workshop; affiliation with UCLA is not required.

**Applied Survey Data Analysis in Stata, Monday, May 24 from 1 to 4 p.m. PDT**

Zoom registration required: https://ucla.zoom.us/meeting/register/tJUrcO2qpjopHdZ1iMHcg9ksIr0czZ3ixKiL

This workshop will discuss the following topics:

• how complex survey data are different from other types of data

• how to do to basic descriptive statistics with continuous and categorical variables

• how to make descriptive graphs with complex survey data

• how to run a variety of regression models, including linear, binary logistic, ordinal logistic, multinomial logistic and count regression models with complex survey data, including how to graph interactions in such models

• how to analyze subpopulations.

Familiarity with the use of Stata and basic data analysis concepts is recommended.

## 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
- (NEW) 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
- 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)
- Repeated Measures Analysis in SPSS
- Using the SPSS Mixed Command
- Graphics using SPSS

**Mplus and Latent Variable Analysis**

- (NEW) Introduction to Structural Equation Modeling (SEM) in R with lavaan
- Confirmatory Factor Analysis with in R with lavaan
- Decomposing, Probing and Plotting Interactions in R
- Introduction to R
- R Markdown Basics
- Introduction to ggplot2
- R Data Management
- Repeated Measures Analysis in R
- Introduction to Regression in R
- Survey Data Analysis with 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**