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…
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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…
Read More
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…
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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…
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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…
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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…
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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…
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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…
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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…
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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…
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