Multiple Regression and Other Foundational Topics

S3E22: The Mättrix Part 1: Defining & Manipulating Matrices

In this first of two episodes, Greg & Patrick lay the foundations of matrix algebra, mathematically and geometrically, and start connecting these important underlying ideas to statistics. Along the way, they also discuss STDs, the 110 to the 10 to the 405, mystics, skin bags of water, vector Victor, Tac flashlights on misty nights, remembering […]

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S3E21: A Low-Resolution Discussion of Sampling Distributions

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

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S3E17: Logistic Regression: 2 Logit 2 Quit

Greg and Patrick explore the generalized linear model as a powerful framework for building regression models for binary and other discretely distributed dependent variables. Along the way they also discuss stealing property, statistical conspiracy theories, mic drops, coming uncorked, getting punched by biostatisticians, big logistic, tapping out, the Oakland Raiders, being 8.5 feet tall, sheep

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S3E09: Semi-Partially Clarifying Measures of Association in Regression

Patrick and Greg answer a mailbag question about some foundational principles of regression and correlation, specifically the differences among correlation, standardized regression weights, semi-partial correlations, and partial correlations. They also check in with someone from Season 2: Amanda Montoya’s undergrad mentee, Kat. Along the way, they also mention: Ap Olo Gies, mocking by text, particle

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S3E04: Two Time Point Data: What Is Your Quest?

Patrick and Greg talk about the potential advantages and disadvantages of alternative approaches to analyzing two time-point data. They discuss traditional models for raw and residualized change scores, and describe how each of these remains baked into the soul of contemporary models for repeated measures data.  Along the way they also mention: 24 inch pizza

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S3E02: Johnson-Neyman Regions of Significance

In this episode, Patrick leads Greg and the rest of us through the incredibly cool and powerful topic of regions of significance, a way to help unpack under what moderating conditions treatments and variable relations are statistically significant. Along the way, they also mention: parallelism, Olivia Newton-John, going to the wrong church, laws in Vermont,

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S2E30: ‘Always Center Your Predictors!’ And Other Sh*t My Advisor Says

Greg and Patrick explore the many interesting issues related to centering predictor variables prior to analysis, both in the standard regression model and in the multilevel model. Along the way they also discuss honking Diet Coke through your nose, rashes, hostage negotiation, reading at seven months of age, dealer’s choice, Coors Light, Galapagos tortoises, friendly

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