Repeated measures ANOVA doesn’t cut it for many repeated measures situations, but do you always need mixed models instead?
Stage 3
Member Training: Marginal Models for Repeated Measures Data
September 2nd, 2025 by TAF Support
Member Event: Count Models Accelerator
July 30th, 2025 by Karen Grace-Martin
You’ll be excited to hear we’re doing another Statistics Skills Accelerator for our Statistically Speaking members: Count Models.
Stats Skills Accelerators are structured events focused on an important topic. They feature Stat’s Amore Trainings in a suggested order, as well as 
live Q&As specific to the Accelerator.
In August, our mentors will be running a new Accelerator. The first Q&A is August 6, 2025 at 3 pm ET, hosted by Jeff Meyer.
Count models are used when the outcome variable in a model or group comparison is a discrete count:
- Number of eggs in a clutch
- Number of days in intensive care
- Number of aggressive incidents in detention
Count models come in a few types, and any of these can also be used for rates:
- Poisson Regression is the simplest and is the basis for all the other models, but its assumptions are rarely met with real data.
- Negative Binomial regression adds an extra parameter to a Poisson regression measure the extra variance that often occurs in real data.
- Truncated count models work when the lowest values (often just zero) cannot occur. This happens when a count has to occur in order to be part of the population of interest.
- Zero inflated count models are used when there are more zeros than expected. For this model, some zeros could have been something else and others couldn’t.
- Hurdle models also work when there are more zeros than expected, but the process of having a zero is different. In these models, there is an actual “hurdle” one has to pass in order to have a non-zero count.
- Logistic regression, when your count is out of of maximum number.
In this accelerator, learn about the different types of count models, how to understand their results, how to apply them to rates, and how to choose among them.
Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and is a combination of watching recorded trainings and live events.
Member Training: Cubic Splines
July 2nd, 2025 by TAF Support
Splines provide a useful way to model relationships that are more complex than a simple linear function. They work with a variety of regression models.
Member Training: Confirmatory Factor Analysis
March 3rd, 2025 by TAF Support
Member Training: Exploratory Factor Analysis
February 1st, 2025 by Karen Grace-Martin
Many variables we want to measure just can’t be directly measured with a single variable. Instead you have to combine a set of variables into a single index.
But how do you determine which variables to combine and how best to combine them?
Exploratory Factor Analysis.
EFA is a method for finding a measurement for one or more unmeasurable (latent) variables from a set of related observed variables. It is especially useful for scale construction.
In this webinar, you will learn through three examples an overview of EFA, including:
- The five steps to conducting an EFA
- Key concepts like rotation
- Factor scores
- The importance of interpretability
Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
About the Instructor
Karen Grace-Martin helps statistics practitioners gain an intuitive understanding of how statistics is applied to real data in research studies.
She has guided and trained researchers through their statistical analysis for over 15 years as a statistical consultant at Cornell University and through The Analysis Factor. She has master’s degrees in both applied statistics and social psychology and is an expert in SPSS and SAS.
Just head over and sign up for Statistically Speaking. You'll get access to this training webinar, 130+ other stats trainings, a pathway to work through the trainings that you need — plus the expert guidance you need to build statistical skill with live Q&A sessions and an ask-a-mentor forum.Not a Member Yet?
It’s never too early to set yourself up for successful analysis with support and training from expert statisticians.
Member Training: Introduction to Binary Logistic Regression
December 3rd, 2024 by TAF Support
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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