Quantitude

In this week's episode the employees of Quantitude International, including some very special guests, treat Greg and Patrick to a Secret Santa (ahem....secret Father Christmas) office party that they…

In today’s episode, Patrick and Greg talk about those critical distributions that often go un-discussed -- noncentral distributions -- including their relation to the more familiar central distributi…

In today’s episode, Greg and Patrick talk about model under-, just-, and over-identification, starting with the algebraic foundations and moving into implications for the practice of structural equat…

 In today's episode Patrick and Greg talk about that sweet spot between panel designs and time series designs, intensive longitudinal data — both the logistical and analytical challenges, but more im…

In this week's episode Greg and Patrick get to explore modern methods for missing data analysis while belaboring quotes from Top Gun with their guest Craig Enders from the University of California at…

In this week's Halloween-themed episode, Patrick and Greg have fun talking about things in their academic jobs that scare them, from things that are a little scary to things that they find absolutely…

In this week's episode Greg and Patrick talk about the frequent gap between research questions and methods and ways to think about reengineering your variables, your parameters, or your entire model …

In this week's episode Patrick and Greg spend a wonderful, if not at times awkward, hour talking with Dan Bauer about the genesis, application, and future directions of what may be the world's worst …

In this week's episode Greg and Patrick talk about partial least squares, a technique that resembles structural equation modeling but with a lot of flexibility, including but not limited to its abili…

In this week's episode Patrick and Greg explore the often neglected method of two-stage least squares; they take a walk down memory lane to explore its origins and then drag it kicking and screaming …

This week Patrick and Greg talk about maximum likelihood estimation: what it is, where it comes from, how it works, what it can do, and what it can't do. Along they way they also mention tour-bombing…

In the opening episode to Season 4, Greg and Patrick delve into ordinary least squares estimation: where it came from, what it attempts to achieve, and where it can take us from here. Along the way t…

In this, their 100th episode and Season 3 finale, Greg and Patrick talk about the challenges and joys of a career in academia. Helping to ensure that we don’t let the bastards grind us down are the v…

In this week's episode Patrick and Greg get to hang out with Noah Greifer from the Institute for Quantitative Social Sciences at Harvard University to delve into the fascinating world of propensity s…

In this week's episode, Greg and Patrick talk about information theory: what it is, where it comes from, how it works, and how it can be used to make comparative model inferences. Along the way we al…

In this week's episode Greg and Patrick discuss the sometimes terrifying issue of fungible weights in multiple regression and structural equation modeling in which selecting a trivially worse criteri…

In this week's episode Patrick and Greg explore Sewall Wright's path tracing rules as an alternative to covariance and matrix algebra, including how the rules work and the tremendous insights they ca…

In this week's episode Greg and Patrick continue their discussion from last week in The Mättrix Part Deux, exploring the magic of matrices including estimation, eigenvalues, and eigenvectors. Along t…

In this first of two episodes, Patrick and Greg lay the foundations of matrix algebra, mathematically and geometrically, and start connecting these important underlying ideas to statistics. Along the…

In this week's episode Greg and Patrick discuss the critical distinction between sample distributions and sampling distributions, and explore all the different ways in which sampling distributions ar…