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…

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# Statistics

## Decomposing and Visualizing Interactions in R

In regression, we are often interested in an interaction, which is the modification or moderation of the effect of an independent variable by another. Understanding interactions involves interpreting the regression coefficients, estimating and testing simple effects and their differences, and visualizing the interaction. This workshop will teach you how to do all of these thing…

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## Missing Data in R

The purpose of this seminar is to discuss techniques and introduce some useful packages in R for handling missing data. In particular, we will focus on multiple imputation and how to perform it using the R package, mice: “Multivariate Imputation by Chained Equations”. As prerequisite to this seminar, we suggest participants have basic knowledge in…

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## Introduction to Meta-analysis in Stata

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…

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## Introduction to Regression in R

This seminar will introduce some fundamental topics in regression analysis using R in three parts. The first part will begin with a brief overview of the R environment, and then simple and multiple regression using R. The second part will introduce regression diagnostics such as checking for normality of residuals, unusual and influential data, homoscedasticity…

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## Introduction to Mplus

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…

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## Introduction to R

This workshop introduces the functionality of R, with a focus on data analysis. Topics include: using RStudio, R coding basics, importing and cleaning data, simple data analysis functions, and brief introductions to R graphics (base and ggplot2) and RMarkdown. This workshop is interactive with coding exercises throughout. Any questions about this workshop can be emailed…

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## Statistical Writing

Workshop description and Zoom registration link coming soon!

## Introduction to Spatial Statistics with Python

Registration link: https://ucla.zoom.us/meeting/register/tJwkdu6hqj4sG9ZioB0tM8VuXxA44AWGc6W- Visual interpretations are meaningful ways to determine spatial trends in our data. However, underlying factors—such as inconsistent geographies, scale, data gaps, overlapping data—have the potential to produce incorrect assumptions, as valuable information may be conveniently hidden from the visual output. One way to address this issue is to amend your visual output…

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## Multiple Imputation in R

Please REGISTER in advance here. Workshop will be conducted in Zoom in PST time. Invites are sent out the day before the workshop. The purpose of this workshop is to discuss commonly used techniques for handling missing data and common issues that could arise when these techniques are used. In particular, we will focus…

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