Quantitude

Patrick and Greg discuss the rise of machine learning in the social sciences with guest Doug Steinley, Professor in the Department of Psychology at the University of Missouri at Columbia and current …

In this week's episode Greg and Patrick have a wonderfully engaging conversation with social network analysis expert Tracy Sweet who is an Associate Professor in the Department of Human Development a…

In this week's episode Patrick and Greg discuss latent means models to conduct group mean comparisons while controlling for measurement error, which gives you more power and more accurate standardize…

Greg and Patrick explore the generalized linear model as a powerful framework for building regression models for binary and other discretely distributed dependent variables. Along the way they also m…

In today's episode, Patrick and Greg use the context of COVID rapid tests to discuss issues of sensitivity, specificity, positive and negative predicted values, and the generally questionable utility…

In today's episode Greg & Patrick discuss the causes, consequences, and potential solutions associated with negative residual variances in factor analyses, a condition commonly called a Heywood case.…

Patrick and Greg, perched in a glass booth high above New York's Times Square, ring in 2022 with the help of some friends by counting down quantitative New Year’s resolutions.

Along the way they also …

In today's episode, Greg and Patrick talk about the rich array of models for testing hypotheses about mutual influences between people within a dyadic relationship. Along the way they also mention bo…

Patrick and Greg have an in-depth conversation with Derek Briggs, from the University of Colorado, about his new book exploring the fascinating and at times uncomfortable history of measurement and t…

Greg and Patrick talk about median splits and other ways that continuous variables might be categorized to simplify analyses, and the often very high cost of doing so. Along the way they also mention…

Patrick and Greg discuss the often forgotten importance of observation and exploration for the purpose of suggesting patterns and forming hypotheses, which can later be refined and rigorously tested …

Patrick and Greg answer a mailbag question about some foundational principles of regression and correlation, specifically the differences among correlation, standardized regression weights, semi-part…

In today's episode Patrick and Greg talk about statistical degrees of freedom: what they represent, how they are computed, and the importance they play in daily life. Along the way they also mention …

In this episode, Greg and Patrick discuss the many places where researchers make decisions throughout the research process, and they weigh the pros and cons of those researchers having such decision-…

In today's episode Patrick & Greg talk about the use of item parcels in latent variable modeling: what they are, what might motivate you to use them, and what unexpected complications can arise. Alon…

What starts as a friendly check-in with our intern Ethan McCormick in the Netherlands turns into Ethan's Pop Quiz Revenge around the themes of statistical paradoxes and distributions. Along the way, …

Patrick and Greg talk about the potential advantages and disadvantages of alternative approaches to analyzing two time-point data. They discuss traditional models for raw and residualized change scor…

Greg and Patrick discuss Principal Components Analysis: what it is, what it absolutely isn't, and what kind of cool things it can do in its own right. Along the way, they discuss Twinkle Twinkle Litt…

In this episode, Patrick leads Greg and the rest of us through the incredibly cool and powerful topic of regions of significance, a way to help unpack under what moderating conditions treatments and …

In the inaugural episode of Season 3, Patrick and Greg argue (more than usual) about statistical conclusion validity: what it is, what affects it, and how it fits in with other types of validity. Alo…