Regression models, such as linear, logistic, time to event, and mixed models, measure the strength of the association between the dependent variable and the independent variables.
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Stage 3
Member Training: A Guide to Models for Causal Inference
January 31st, 2026 by TAF Support
Member Training: Principal Component Analysis
January 1st, 2026 by TAF Support
When you’re working with many correlated variables, they get too unwieldy to use individually.
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Member Training: Marginal Models for Repeated Measures Data
September 2nd, 2025 by TAF Support
Repeated measures ANOVA doesn’t cut it for many repeated measures situations, but do you always need mixed models instead?
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
