In this episode Patrick and Greg discuss the challenges of having ordered categorical data, as well as the seemingly magical limited information and full information analytical options to deal with such data. Along the way they also discuss sky cranes, the Mars Climate Orbiter, metric vs. imperial units of measurement, Lockheed-Martin, left hands and right […]
S2E27: (re)Connecting With Discrete Data Read More »
In this episode Greg and Patrick attempt to resolve long festering relationship issues that arise between the multilevel modeling and structural equation modeling approaches to growth curve analysis. Along the way they also discuss first dates, Jets and Sharks, Cubs and Cardinals, Montagues and Capulets, Tsingtao Beer, Thunderdome, stupid LISREL tricks, pressure math, dirty secrets,
S2E26: MLM vs. SEM: Opportunities for Growth Read More »
In this episode Patrick and Greg talk about the dreaded but often very real case of having a small sample size: what you should watch out for, and what options you have to squeeze the most information and inferential potential from your precious data. Along the way they also mention Name That Tune, Space Mountain,
S2E25: Options for Small Samples Read More »
In this episode Greg and Patrick explore the freakish and terrifying topic of equivalent models, particularly as they arise within the structural equation modeling analytical framework. Along the way they also discuss rinsing toes, palindromes, anagrams, being a tad unquiet, under-teaching, double-secret probation, scary cousins, sausage makers, Tribbles, empty beer bottles, Hard Core History, a
S2E24: The Equivalent Models Problem Read More »
Patrick and Greg talk about variability — both within individuals and within groups — as a source of really interesting and often overlooked research questions, to complement our well-developed skillset for studying means. Along the way, they also mention: Natatoriums, finding your spot, picking at a scab, the Polkaholics, Location Scale models, high-fiving statisticians, Inception,
S2E23: Research Questions About Variability Read More »
In this episode Greg and Patrick embark on a sometimes unhinged discussion of outlying and influential observations: where do they come from, how are they identified, and what do we do with them. Along the way they also discuss the outlier bell, stubbornness, pre-holiday grievances, Polly, Sesame Street, being more less likely, Greg’s freak brother,
S2E22: Outliers — And Then Things Got Weird Read More »
In this episode Patrick and Greg talk about latent variables: what they are, why we care, and under what circumstances we can analyze them directly. Along the way they also discuss: BWI, dadgic, Patrick’s bromance, the economy, Chris Botti, inter-planetary probes, Gronk, 118 degree dry heat, the evil eye, and Dora the Explorer.
S2E21: Yes, Virginia… There ARE Latent Variables Read More »
Greg and Patrick again subcontract out their own work by inviting a range of experts from different disciplines to share their perspectives on the future of teaching quantitative methods. They also discuss revenge, cryogenics, evacuation com…., American Idiot, 11 reasons why we blink, being hardly sorry, Googling how to fly a 737, machine directed latent
S2E20: The Future of Teaching Quantitative Methods Read More »
In today’s episode, Patrick and Greg talk about the tenure process: what it is, why it exists, how they see it, and some thoughts that might be helpful on the journey, fully realizing that institutions and fields are different, so your mileage may vary. Along the way, they also mention Fermat’s Theorem, Ten Year, The
S2E19: Pulling Back The Curtain On Tenure Read More »
In this episode Patrick and Greg compare and contrast multiple regression and the structural equation model and argue that although regression has brought us far, there are numerous reasons to turn to the SEM to continue to drive us forward. Along the way they also address gad flies, the Louisiana Purchase, Kool-Aid, high school friends,
S2E18: Regression — Like That Old High School Friend You’ve Outgrown Read More »
