Training Contents


Name
Description
Content
Keywords
Author
Running the Statistical Gauntlet in R
A series of examples of statistical tests in R, aimed to help train researchers in understanding statistical output, graphs, and conclusions.
R, statistics, t-test, ANOVA, regression
Dr. Mark Williamson

Linear Regression Module I
A quick overview of linear regression; includes quick examples and assessment.
regression, R, SAS, overview
Dr. Mark Williamson

Linear Regression Module II
A more detailed explanation and practice of linear regression; includes step-by-step examples and assessment.
regression, R, SAS, theory, descriptions
Dr. Mark Williamson

Linear Regression Module III
A deeper look at more advanced topics in linear regression; includes live examples and assessment.
regression, R, SAS, STATA, generalized linear mixed model, longitudinal analysis, structural equation modeling
Dr. Mark Williamson

Exploratory Data Analysis Module I
A quick overview of exploratory data analysis; includes quick examples and assessment.
exploratory data analysis, graphs, statistical tests
Dr. Mark Williamson

Exploratory Data Analysis Module II
A more detailed explanation and practice exploratory data analysis; includes step-by-step examples and assessment.
exploratory data analysis, R, SAS, theory, descriptions, graphs, statistical tests
Dr. Mark Williamson

Exploratory Data Analysis Module III
A deeper look at more advanced topics in exploratory data analysis.
exploratory data analysis, R, SAS, graphs, statistical tests, multiple dimensions, variable selection, complex plots
Dr. Mark Williamson

Power Analysis in G*Power
An introduction to running power analysis in G*Power for a variety of statistical models; includes descriptions, instructions, and examples
power analysis, sample size, gpower
Dr. Mark Williamson

Power Analysis in R
An introduction to running power analysis in R for a variety of statistical models; includes descriptions, instructions, and examples.
power analysis, sample size, R
Dr. Mark Williamson

Power Analysis in R: GLMMs
An introduction to generalized linear mixed models, how to create them in R, how to use simulation to obtain sample size estimates for them, and a series of examples.
power analysis, sample size, R, generalized linear mixed model, simulation
Dr. Mark Williamson

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