Membership Webinars

Meta-analysis allows us to synthesize the results of separate studies. The goal is to assess the mean effect size and also heterogeneity – how much the effect size varies across studies.  (more…)

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In this nearly 6-hour tutorial you will learn menu-based R libraries so you can use R without having to fuss with R code. These libraries don’t cover everything R can do, but they do quite a bit and can set you up to make running R much easier.

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The great majority of all regression modeling explores and tests the association between independent and dependent variables. We are not able to claim the independent variable(s) has a causal relationship with the dependent variable. There are five specific model types that allow us to test for causality. Difference in differences models are one of the five.

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Have you ever wondered why there are so many different types of experimental designs, and how a researcher would go about choosing among them to best address their research questions? (more…)

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Post-hoc tests, pairwise or other linear contrasts, are typical in an analysis of variance (ANOVA) setting to understand which group means differ. They incorporate p-value adjustments to avoid concluding that group means differ when they actually do not. There are several adjustments that can be considered for conducting multiple post-hoc tests, including single-step and stepwise adjustments. (more…)

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If you’ve been doing data analysis for very long, you’ve certainly come across terms, concepts, and processes of matrix algebra.  Not just matrices, but:

• Matrix addition and multiplication
• Traces and determinants
• Eigenvalues and Eigenvectors
• Inverting and transposing
• Positive and negative definite

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