Øystein Sørensen

@osorensen.bsky.social

Professor in Biostatistics, Department of Psychology, University of Oslo

Ecological momentary assessment data are everywhere in the social and medical sciences. DSEM offers a great way of analyzing them, by coupling vector-ARIMA models for each individual through Bayesian priors, under the assumptions that two people in general at least share some similarity.

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Dynamic structural equation modeling is very popular for ecological momentary assessment data, but the original algorithm contains an unnecessary bottleneck making latent variable modeling challenging. Here I propose the NUTS-Kalman algorithm, which replaces within-level sampling with a

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Ecological momentary assessment data are everywhere these days. In psychology, dynamic structural equation models (DSEMs) are particularly attractive for analyzing such data. In this paper Ethan McCormick and I show how you can easily incorporate nonlinear trends and cycles using splines.

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Oh joy! BDR found a subtle warning on Fedora with gcc15 with very strict compiler flags that threatened to kick my galamm #rstats pkg out of CRAN by Saturday. After a week of headscratching I managed to set up my old Ubuntu laptop to reproduce the error :-)

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Preprint! The Bayesian Mallows model is a very flexible model for analyzing rank and preference data, and has been applied across a large number of domains. In many cases, however, the data naturally arrive sequentially in time. Existing Metropolis-Hastings algorithms scale poorly in this case

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Does anyone know of a good quantitative methods textbook for the social sciences? Ideally not too tied to a given analysis program, and not too much ANOVA stuff. I'm teaching a course which covers experimental design, multiple regression, mixed models.

Hello everyone, I'm Lea Michel, a 3-year PhD working at the Donders Institute with @rogierk.bsky.social on the interaction between grey and white matter in supporting cognitive development during childhood/adolescence. I'm also invested in science communication, open science and greener research 🌱