## Workshops for Spring, 2020

**Introduction to ggplot2**, Monday, April 27 from 1 to 4 p.m. via Zoom**
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Description: The ggplot2 package is a widely-used and well-supported system for creating eye-catching graphics in R. In this interactive workshop, you will learn the underlying grammar of graphics that forms the philosophical framework of ggplot2, giving you the power to create publication-quality figures intuitively. The workshop is interactive, in which attendees are encouraged to participate in R coding to create their own statistical graphics.

The notes for the workshop are here. This workshop will be hands-on. Attendees should have R and R Studio installed on their computers prior to the start of the workshop.

Attendance is restricted to researchers from the University of California. The information for the Zoom meeting will be sent the day before the workshop.

Sign up at https://idre.ucla.edu/calendar-event/introduction-to-ggplot2-3

**Introduction to Mplus 8**, Monday, May 4 from 1 to 4 p.m. via Zoom

Description: Mplus is a powerful statistical package used for the analysis of latent variables. Among the kinds of analysis it can perform are exploratory factor analysis, confirmatory factor analysis, latent class analysis, latent growth curve modeling, structural equation modeling and multilevel modeling. The program can handle a combination of categorical and continuous variables and often permits missing data. It integrates these analyses into a single framework where you can combine techniques like growth curve modeling and latent class analysis to ask unique questions, such as “Are there latent classes among the growth trajectories?”. Mplus runs under Windows. This workshop is designed for people who are just getting started using Mplus to orient them to the nuts and bolts of using this package. These notes are the scripts for the workshop. The notes are not meant to be a Mplus textbook or substitute for the reference manual.

The notes for the workshop are here. This workshop will not be hands-on.

Attendance is restricted to researchers from the University of California. The information for the Zoom meeting will be sent the day before the workshop.

Sign up at https://idre.ucla.edu/calendar-event/introduction-to-mplus-2

**R Data Management**, Monday, May 11 from 1 to 4 p.m. via Zoom

Description: This workshop introduces R packages and functions that help users import, transform and manage their data in preparation for analysis. The seminar focuses on the “tidy data” philosophy encouraged y the “tidyverse” collection of R packages, but draws on other packages for useful functions as needed. Topics include data import, transforming variables, string functions, missing data, merging datasets, reshaping data, grouped data processing, and looping.

The notes for the workshop are here. This workshop will not be hands-on.

Attendance is restricted to researchers from the University of California. The information for the Zoom meeting will be sent the day before the workshop.

Sign up at https://idre.ucla.edu/calendar-event/r-data-management

**A Practical Introduction to Exploratory Factor Analysis (EFA) in SPSS**, Monday, May 18 from 1 to 4 p.m. via Zoom

Description: This workshop will give a practical overview of exploratory (EFA) in SPSS. Topics to be covered include factor extraction, principal components analysis, estimation methods, factor rotation, refining the factor structure, and generating factor scores for subsequent analyses.

The notes for the workshop are here. This workshop will not be hands-on.

Sign up at https://idre.ucla.edu/calendar-event/a-practical-introduction-to-factor-analysis-in-spss

**Power and Sample Size in Stata**, Tuesday, May 26 from 9 a.m. to 12 noon via Zoom

In this talk I introduce the concepts and jargon of power and sample size calculations such as alpha levels, power, and minimum detectable effect sizes. I do several simple calculations manually and then demonstrate how to replicate these calculations using Stata’s -power- commands. Next I demonstrate how to create tables and graphs for power, sample size, and minimum detectable effect sizes for a range of values. We will conclude with a discussion of strategies to increase statistical power.

The second part of the talk demonstrates how to calculate power using simulation methods and how to create your own custom power calculation programs that leverage Stata’s -power- command to create custom tables and graphs. We will work examples that simulate power for a t-test, the interaction term in a linear regression model, and the interaction term in a multilevel model. Along the way you will learn how to create simulated datasets, use Stata’s -simulate- command, and how to write your own Stata commands using -program- and -syntax-.

Sign-up at https://idre.ucla.edu/calendar-event/talk-power-and-sample-size-with-stata-corps-chuck-huber

## 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

- 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 (Version 23)
- 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) 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

**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**