In this week’s episode, Greg and I discuss the amazing world of the empirical bootstrap. We start with inferential testing using business as usual, we describe where that quickly runs into problems, and we explore where bootstrapping does and, importantly, does not help move us forward. Along the way we also discuss midnight in Bangkok, […]
S7E08 Bootstrapping Read More »
In this week’s episode, Greg and Patrick explore the very cool yet often overlooked suite of non-parametric statistical tests. They talk about their strengths and weaknesses and how these might be profitably used in practice. Along the way they also discuss science fairs, spaghetti bridges, don’t take this the wrong way, jazz hamster, the Bernoulli
S7E03 Nonparametric Procedures Read More »
In this week’s episode Greg and Patrick explore the extremely clever yet inexplicably underused method of dominance analysis which offers a set of techniques for determining the relative importance of predictors in a regression model. Along the way they also discuss giving compliments, looking tired, Indy vs. F1, chicken paprikás, Gustav Holst, Fozzie Bear, not
S6E20 Dominance Analysis Read More »
In this week’s episode Patrick and Greg talk about outcomes that are count variables: when you need to worry about them and what you can do about them within your analytical models. Along the way they also mention: Bela Lugosi, Vlad the Impaler, Patrick the Poker, Count Chocula, Count von Count, drunken bar brawls, secret
S6E18 Count Variables Read More »
In this weeks episode Greg and Patrick talk about loglinear models as a clever method to deconstruct the potential dependencies among two or more categorical variables. Along the way, they also discuss Children of the Corn, Mr. Magoo glasses, tighty whities, Fogo de Chão, blinded by hand soap, logarithms as drug mules, Euler Euler Euler,
S6E15 Loglinear Models: Someone Should Have Told You Read More »
In this week’s episode Greg and Patrick talk about group coding approaches, like dummy variables and effect code variables, for helping to analyze group differences within the larger general linear model. Along they way they also discuss hacking up a lung, made for audio faces, walking pneumonia, putting Vicks VapoRub on your feet, cards in
S6E13 Group Codes in GLM: Dummy and Dummier Read More »
In this week’s episode Greg and Patrick explore the fascinating world of suppressor variables which have the nearly magical, yet fully understandable, distinction of being unrelated to the dependent variable yet serving to enhance the predictive utility of other variables in the model. Along the way they also discuss getting the giggles, giving away our
S6E12 Suppression Unrepressed Read More »
In this week’s episode, Greg and Patrick talk about instrumental variables: what they are, how they help to make causal claims, and the many assumptions and challenges associated with them. Along the way they also mention: Festival of Side Dishes, pilot turkeys, gutsy bagpipes, charter schools, drama kids, RCT wieners, Space Force, licking a rainbow,
S6E10 Instrumental Variables (Dad)Rock! Read More »
In this week’s episode, Patrick and Greg discuss the benefits and limitations of generalized estimating equations as an approach to dealing with data that violate the assumption of independence. Along the way they also mention: goat rodeos, haunted houses, jump scares, liberos, Haikyu!!, Whoa Ace!, dadenfreude, Otto, cutting the baguette, this just in, American Idiot,
S6E08 The Statenfreude of Generalized Estimating Equations Read More »
In this week’s episode Greg and Patrick discuss Cattell’s data box and try to better understand what it is, what it is not, and how we might make use of this in practice. Along the way they also discuss illegal knives, baseball cards, the Cubs and the Mariners, bicentennial quarters, how to load a dishwasher,
S6E05 Cattell’s Data Box Read More »
