## Workshops for Winter Quarter, 2019

**Analyzing and Visualizing Interactions in SAS**, Thursday, February 7 from 9 a.m. to 12 noon in Math Sciences 5628 (the Visualization Portal)

Description: In regression, we are often interested in an interaction, which is the modification of the effect of an independent variable by another. To understand the magnitude, direction, and significance of the interaction we need to decompose it into simple effects. Simple effects can be analyzed in three ways, by 1) testing each effect against zero, 2) testing differences among effects, and 3) visualizing each effect with graphs. This seminar will demonstrate how to do all three analyses in SAS PROC GLM / PLM for the following regression models: quadratic, continuous-by-continuous, categorical-by-continuous, categorical-by-categorical, and categorical-categorical-continuous interaction. The notes for the workshop are here. The sign-up link is here.

**Meta-analysis in Stata**, Thursday, February 14 from 9 a.m. to 12 noon in Math Sciences 5628 (the Visualization Portal)

Description: Meta-analysis is the synthesis of results from previous studies. It is used to increase power, obtain a better estimate of an effect size, and sometimes to resolve conflicting conclusions in the literature. In this workshop, we will discuss how the data for a meta-analysis are collected and organized, as well as how such data are analyzed and graphed. We will also discuss some of the limitations meta-analysis and what should be included in a meta-analysis for publication. The notes for the workshop are here. The sign-up link is here.

**Introduction to Regression in R**, Thursday, February 21 from 9 a.m. to 12 noon in Math Sciences 5628 (the Visualization Portal)

Description: 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 does not teach regression, per se, but focuses on how to perform regression analyses using R. However, it gives a very brief review on the theoretical background as necessary. It is assumed that participants have had at least a one quarter/semester course in regression (linear models) or a general statistical methods course that covers simple and multiple regression and have access to a regression textbook that explains the theoretical background of the materials covered in this seminar. These materials also assume basic familiarity with R, for example that you have taken the Introduction to R seminar or have equivalent knowledge of R. The seminar begins with simple regression and generalize the methods to multiple regression, followed by regression diagnostics, and regression with categorical predictors. The notes for the workshop are here. The sign-up link is here.

**R Markdown Basics**, Thursday, February 28 from 9 a.m. to 12 noon in Math Sciences 5628 (the Visualization Portal)

Description: 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 notes for the workshop are here. The sign-up link is here.

## Past Classes and Workshops Available Online

- Introduction to Stata 15
- Stata Data Management
- Regression with Stata
- Logistic Regression with Stata
- Beyond Binary Logistic Regression with Stata
- Multiple Imputation in Stata 14
- Introduction to Survey Data Analysis
- Applied 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 SPSS Syntax, Part1 (using SPSS version 21)
- Introduction to SPSS Syntax, Part 2 (using SPSS version 21)
- Regression with SPSS
- Introduction to Regression with SPSS (Version 23)
- Principal Components (PCA) and Exploratory Factor Analysis (EFA) with SPSS
- A Practical Introduction to Factor Analysis
- Repeated Measures Analysis in SPSS
- Using the SPSS Mixed Command
- Graphics using SPSS

**Mplus and Latent Variable Analysis**

- Introduction to R
- R Markdown Basics
- Introduction to ggplot2
- R Data Management
- Repeated Measures Analysis 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**