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.
logistic regression
Member Training: Analyzing Longitudinal Data: Comparing Regression and Structural Equation Modeling Approaches
July 2nd, 2024 by TAF SupportMember Training: Linear Model Assumption Violations: What’s Next?
June 30th, 2023 by guest contributer
What do you do if the assumptions of linear models are violated?
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Member Training: Interactions in Poisson and Logistic Regression
May 1st, 2023 by TAF SupportInteractions in statistical models are never especially easy to interpret. Throw in non-normal outcome variables and non-linear prediction functions and they become even more difficult to understand. (more…)
The Difference Between the Bernoulli and Binomial Distributions
February 8th, 2023 by Kim Love
You might already be familiar with the binomial distribution. It describes the scenario where the result of an observation is binary—it can be one of two outcomes. You might label the outcomes as “success” and “failure” (or not!). (more…)
Member Training: Multinomial Logistic Regression
December 30th, 2022 by TAF SupportMultinomial logistic regression is an important type of categorical data analysis. Specifically, it’s used when your response variable is nominal: more than two categories and not ordered.
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Guidelines for writing up three types of odds ratios
December 6th, 2021 by Karen Grace-MartinOdds ratios have a unique part to play in describing the effects of logistic regression models. But that doesn’t mean they’re easy to communicate to an audience who is likely to misinterpret them. So writing up your odds ratios has to be done with care. (more…)