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Statistics

Zero-inflated and Hurdle models for Count Data in R

This workshop introduces zero-inflated poisson, zero-inflated negative binomial, and hurdle models for count data, which are two-part models used when more zeros are found in the data than expected with…

Zero-inflated and Hurdle models for Count Data in R

This workshop introduces zero-inflated poisson, zero-inflated negative binomial, and hurdle models for count data, which are two-part models used when more zeros are found in the data than expected with…

Zero-inflated and Hurdle models for Count Data in R

This workshop introduces zero-inflated poisson, zero-inflated negative binomial, and hurdle models for count data, which are two-part models used when more zeros are found in the data than expected with…

Introduction to Linear Regression in R

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…

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…

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…

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…

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…

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…

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…