🚨Writing to say that I am actively recruiting PhD students in the clinical -or- behavioral, psychiatric, and statistical genetics program (BPSG) at CU Boulder for a Fall 2025 start date. My lab focuses on genomic methods development and applications to psychiatric and aging outcomes (e.g., dementia)

The best writing advice I've ever gotten is to remember that the first draft is where you explain it all to yourself and then the second draft is where you explain it all to your readers.

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I love this title so much

📊When teaching or giving a talk, do you like presenting plots step by step, revealing e.g. one group at a time? This is often useful for walking through complex results. I made a R package that makes it extremely easy to do this! ggreveal: Reveal a ggplot incrementally #rstats#dataviz#ggplot2

There is a pernicious thing I've noticed which starts from the very valid observation that being marginalised means being you are often the target of assholes and ends up at the totally invalid conclusion that marginalised people can't be assholes (or that if they are, it's warranted). 1/

Rough time for the reciprocal effects crowd: Cross-lagged panel models can’t reliably establish cross-lagged effects. Need big N, need time invariant effects, & equivalent models can't distinguish whether they exist. from Bengt Muthén & Tihomir Asparouhov www.statmodel.com/download/Rec...

A new paper in Psychometrika by Dr Chares Rahal et al. explores how the InterModel Vigorish can be used in psychometrics to easily compare predictive systems in dollar denominated terms ⚖️ link.springer.com/article/10.1...@leverhulme.bsky.social@klint.bsky.social@mijke.bsky.social

The InterModel Vigorish as a Lens for Understanding (and Quantifying) the Value of Item Response Models for Dichotomously Coded Items - Psychometrika

The deployment of statistical models—such as those used in item response theory—necessitates the use of indices that are informative about the degree to which a given model is appropriate for a specif...

I’ll be leading a 4-day online (synchronous) seminar on SEM with categorical data June 18-21. Please share this announcement with anyone who may be interested.

Structural Equation Modeling with Categorical Data Workshop

This online statistical training with Wes Bonifay presents a comprehensive treatment of structural equation modeling (SEM) for binary and ordinal (categorical) outcomes.

I suspect the concept of measurement invariance makes no sense for casual indicator models. The whole idea is that two people who have the same level of a factor should have the same expected response pattern. That only works if the items are reflective.