In this week’s episode Greg and Patrick talk all about Simpson’s Paradox: what it is, examples of where it occurs in real life, and why we might not really need to think about it as a paradox at all. Along the way they also discuss Apple Vision, The Simpsons predicting the future, sitting too close […]
S5E16 Simpson’s Paradox Read More »
In this week’s episode Greg and Patrick take a walk down memory lane to rediscover classical test theory, although they revisit this through the lens of modern latent variable models. They describe how these classical methods are actually highly restricted latent measurement models and they explore how these restrictions can be relaxed and even tested.
S5E15 Classical Test Theory (in bed) Read More »
In this week’s episode Greg and Patrick launch a new occasional series called Stuff You Should Know. The topic for today is regression to the mean: what the heck is it, how does it arise in every day life, and what can we do about it. Along the way they also discuss the space-time continuum,
S5E14 Regression to the Mean Read More »
In this week’s episode Greg and Patrick talk about confidence intervals: symmetric and asymmetric, asymptotic and bootstrapped, how to interpret them, and how not to interpret them. Along they way they also discuss tire pressure gauge mysteries, conference travel reimbursement, phases of the moon, gyroscopic effects, baseball walk-of-shame, why people hate us, settling out of
S5E13 The Confidence Interval’s Tale Read More »
In this week’s episode Greg and Patrick have great fun talking about meta-analysis with Paschal Sheeran, a social psychologist from the University of North Carolina at Chapel Hill. He describes what meta-analysis is, what it offers, and how to apply it in your own work. Along the way they also discuss taking off into the
S5E12 Meta-Analysis With Paschal Sheeran Read More »
In this week’s episode, marking the fifth Quantitude Holiday Celebration, Greg and Patrick argue about their favorite holiday movies, including whether Die Hard counts as one or not; they then proceed to discuss several statistical ideas that also seem to Die Hard. Along the way they talk about so much gibberish that we don’t even
S5E11 Statistical Ideas That Die Hard Read More »
In this week’s episode Greg and Patrick explore alternative parameterizations of the SEM-based latent curve model to capture various forms of nonlinearity, some that are approximations and others that are exact. Along the way they also discuss Swifties, remastering your life, bull testicles, the world’s worst RA job, Yerkes-Dodson law, show a little ankle, the
S5E10 Nonlinear Latent Growth Curve Models (Taylor’s Version) Read More »
In today’s episode Greg and Patrick talk about regularization, which includes ridge, LASSO, and elastic net procedures for variable selection within the general linear model and beyond. Along the way they also mention Bowdlerizing, The Family Shakespeare, disturbance in the force, McNeish on his bike, Spandex, C’mon guys wait up, the altar of unbiasedness, Curranizing, shooting arrows, stepwise
S5E09 Regularized Variable Selection Methods Read More »
In today’s episode, Greg and Patrick dig into Confirmatory Composite Analysis, a very clever way to get formative factors and their causal indicators into the traditional structural equation modeling framework, along with any other latent factors and their effect indicators that might already be in the model. Along the way they also discuss full-contact Wordle,
S5E08 Confirmatory Composite Analysis: Enter the Hexagon Read More »
In today’s episode, Patrick and Greg talk about the challenge of having causal indicators of formative factors within an analytical framework that is historically dominated by effect indicators and latent factors — and the critical importance of getting your arrows right. Along the way they also mention: self help books, habits, Hagrid and the giants,
S5E07 Perspectives on Formative Factors & Causal Indicators Read More »
