March 2021

S2E29: Multilevel Models — The Often Unnecessary Green Monster

Uncategorized / 2 minutes of reading

Patrick and Greg fulfill a legal obligation to interview the unnecessarily ubiquitous Dr. Dan McNeish of Arizona State University about why you probably don’t need to use multilevel modeling even when you have multilevel data. Along the way they also mention MacNair, safety schools, the Green Monster, driving a Corvette across the country, Compensation Club, […]

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S2E28: McNeish v. Quantitude — Training Quantitative Methodologists

Uncategorized / 1 minute of reading

Pursuant to court order, Greg and Patrick find themselves legally compelled to discuss key aspects of training quantitative methodologists, including knowledge acquisition, knowledge application, and knowledge generation. Along the way, they also mention: Nuckles, too many Dans, onomatopoeia, The One, the number of the day, a big tylenol, bluesheets, Mr. Miyagi, Lunch n Learn, reviewing

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S2E27: (re)Connecting With Discrete Data

Uncategorized / 2 minutes of reading

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

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S2E26: MLM vs. SEM: Opportunities for Growth

Uncategorized / 1 minute of reading

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,

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S2E25: Options for Small Samples

Uncategorized / 1 minute of reading

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,

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S2E29: Multilevel Models — The Often Unnecessary Green Monster

S2E28: McNeish v. Quantitude — Training Quantitative Methodologists

S2E27: (re)Connecting With Discrete Data

S2E26: MLM vs. SEM: Opportunities for Growth

S2E25: Options for Small Samples

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