In this week’s episode Patrick and Greg talk about partial least squares, a technique that resembles structural equation modeling but with a lot of flexibility, including but not limited to its ability to accommodate both reflective and formative constructs. Along the way they also mention dark Red Bubble, Sheeps Kin, snorting SEM, the Coors Light …
S4E04 Partial Least Squares: Straight Outta Uppsala Read More »
In this week’s episode Greg and Patrick 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 into the 21st century for much promising use within the latent variable model. Along the way they also discuss magic …
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 discuss tour-bombing your kid, licking the turtle, Van Halen and AC/DC, orange mustaches, brandy snifter pong, bus #27, Ronnie Fisher, why …
S4E02 Underachievers, Overachievers, & Maximum Likelihood Estimation Read More »
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 they also discuss Golden Retrievers who are neither gold nor can retrieve, Olivia Newton John, sub-conning out their own …
S4E01 Ordinary Least Squares: Back Where It All Began Read More »
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 scores: what they are, how we obtain them, and how they can be thoughtfully used to strengthen our causal inferences. Along the way …
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 criterion of fit can often lead to radical changes in the corresponding parameter estimates. Along the way they also discuss competitive family Wordle, disambiguation, inflammability, perpitty, being …
S3E25: Fungible Parameter Estimates and Earthquake Waller Read More »
In this week’s episode Greg and Patrick 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 can provide toward understanding a model. Along the way they also discuss the Unabomber, Crate and Barrel, grocery lane profiling, tedious as poop, throwing …
S3E24: The Wright Stuff – The Beauty of Path Tracing Rules Read More »
In this week’s episode Greg and Patrick discuss the critical distinction between sample distributions and sampling distributions and we explore all the different ways in which sampling distributions are foundational to how we conduct research. Along the way they also discuss Starbucks jazz, one item tests, hot pockets, delusions of grandeur, Tetris and Pong, drawing …
S3E21: A Low-Resolution Discussion of Sampling Distributions Read More »
Patrick and Greg discuss the rise of machine learning in the social sciences with guest Doug Steinley who is a professor in the Department of Psychology at the University of Missouri at Columbia and is the current editor of the APA journal Psychological Methods. Along the way they also discuss funeral expenses, Swedish massage, Amy …
S3E20: The Rise of Machine Learning in the Social Sciences with Doug Steinley Read More »
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 and Quantitative Methodology at the University of Maryland. Tracy patiently helps us understand what social network analysis is, and how it can be used to …
S3E19: Social Network Analysis: Making Connections with Tracy Sweet Read More »
