Cross-over trials provide a very powerful approach for comparing two treatment conditions. Research subjects get both treatment conditions, which we will label arbitrarily as A and B.
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Membership Webinars
Member Training: Analysis of Crossover Data
December 1st, 2025 by TAF Support
Member Training: Plot Estimated Marginal Means in R
November 3rd, 2025 by TAF Support
Estimated marginal means (EMMs)—sometimes called least-squares means—are a powerful way to interpret and visualize results from linear and mixed-effects models. Yet many researchers struggle to extract, understand, and plot them.
In this 60-minute hands-on tutorial, participants will learn how to compute, interpret, and visualize EMMs using only base R functions together with the emmeans, car, and lme4 packages. We will start with simple linear models and progress to mixed models with random effects, highlighting how to obtain EMMs, confidence intervals, pairwise contrasts, and publication-ready base R plots. The session emphasizes conceptual understanding and practical code you can adapt immediately to your own analyses.
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
Manolo Romero Escobar is a seasoned statistical consultant and psychometrician with a passion for helping researchers.
Throughout his career, Manolo has worked extensively as a research and statistical consultant. He has served a diverse range of clients including health researchers, educational institutions, and government agencies. With a focus on linear mixed effects modeling, latent variable modeling, and scale development, Manolo brings a wealth of knowledge and experience to every project he undertakes.
Manolo is also proficient in statistical programming languages such as R, SPSS, and Mplus, and has experience with Python and SQL. He is passionate about leveraging technology as an educational and training tool, and he continuously enhances his skills to stay at the forefront of his field.
He holds a B.A. and Licentiate degree in Psychology from Universidad del Valle de Guatemala and a M.A. in Psychology (Area: Developmental and Cognitive Processes) from York University.
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: Outliers and Influential Points
October 3rd, 2025 by Karen Grace-Martin
Outliers. There are as many opinions on what to do about them as there are causes for them.
But there is a lot of bad advice out there about what to do with outliers.
In this training, we’ll take a step back and explore how to think about outliers so you can make good decisions based on your data and model. You’ll learn the different types of outliers and methods for figuring out which type you have. You’ll also learn how to determine whether, and how, they’re influential, and what to do about it.
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: 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.