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Member Training: Interpreting (Even Tricky) Regression Coefficients Workshop

April 1st, 2025 by

In April and May, we’re doing something new: including in membership the workshop Interpreting (Even Tricky) Regression Coefficients with Karen Grace-Martin. 

We’ll be releasing the first 3 of 6 modules in April and modules 4-6 in May and holding a special Q&A with Karen at the end of each month.

If you’ve ever wanted to know how to interpret your results or set up your model to get the information you needed, you’ll love this workshop.

Although it’s at Stage 2 and focuses entirely on linear models, everything applies to all sorts of regression models — logistic, multilevel, count models. All of them.

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Member Training: Confirmatory Factor Analysis

March 3rd, 2025 by

There are two main types of factor analysis: exploratory and confirmatory.

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Member Training: Introduction to Binary Logistic Regression

December 3rd, 2024 by

Binary logistic regression is one of the most useful regression models. It allows you to predict, classify, or understand explanatory relationships between a set of predictors and a binary outcome.
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Member Training: Introduction to Item Response Theory and Rasch Models

November 1st, 2024 by

How do you know if the items of a test are hard or easy; fair or biased; accurate at measuring ability or not? 

Item Response Theory (IRT).

In this training, you will see, with real life examples, how IRT answers these questions to assess a test.

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Member Training: Types of Longitudinal, Repeated Measures, and Time Series

October 2nd, 2024 by

How do you know when to use a time series and when to use a linear mixed model for longitudinal data?

What’s the difference between repeated measures data and longitudinal?
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Member Training: Analyzing Longitudinal Data: Comparing Regression and Structural Equation Modeling Approaches

July 2nd, 2024 by

When analyzing longitudinal data, do you use regression or structural equation based approaches? There are many types of longitudinal data and different approaches to analyzing them. Two popular approaches are a regression based approach and a structural equation modeling based approach.

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