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 distributions, their role in power and sample size determination, and how they are used in assessing data-model fit. Along the way they also mention back porch reading, latent […]
S4E11 The Centrality of Noncentral Distributions Read More »
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 equation modeling. Along the way they also mention shagging cars, new Ferraris, bank statements, prerecorded reactions, Quantitude implied contract, necessary & sufficient, walk of shame, Patrick’s Roz impression,
S4E10 Test Driving Model Identification Read More »
In today’s episode Greg and Patrick talk about that sweet spot between panel designs and time series designs, intensive longitudinal data, both the logistical and analytical challenges but more importantly its tremendous potential. Along the way they also discuss camp fire face-plants, fear of horses, your spare eyelid, polishing your Nobel Prize, ripples in a pond,
S4E09 Intensive Longitudinal Data: Be Careful What You Wish For Read More »
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 Los Angeles. Craig looks back over the past 20 years of developments in missing data analysis to discuss what has worked, what
S4E08 Missing Data: The New State Of The Art With Craig Enders Read More »
In this week’s Halloween-themed episode, Greg and Patrick 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 terrifying. Along the way they also discuss Mrs. Kopicky’s caramel popcorn balls, Wolf of Wall Street, Kenny T, forgetting you’ve told a
S4E07 The Quanti-House of Horror Read More »
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 to help get what you want. Along the way they also discuss living in the dorms, Greek god sculpture rockets, not living in the
S4E06 Building the Model You Want: With Laser Cannons! Read More »
In this week’s episode Greg and Patrick spend a wonderful, if not at times awkward, hour talking with Dan Bauer about the genesis, application, and future directions of the what may be the world’s worst acronym: MNLFA, or moderated nonlinear factor analysis. Along the way they also discuss unsolicited help from teenagers, gold stars, acronyms,
S4E05 Moderated Nonlinear Factor Analysis: A Conversation with Dan Bauer Read More »
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
S4E03 Two-Stage Least Squares Strikes Back Read More »
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 »
