Anyone have insights into why psychology researchers wouldn't want to use or learn about machine learning? I'm curious to hear from editors of methods journals too ... We've heard "great paper, fits our scope, but not a topic our readers would want" from US quant psych methods journals. Why?
Really cool work using penalization to uncover subgroup-specific dynamics in ILD data using VAR.
We have a new preprint! I'm excited to share recent work related to modeling multiple-subject, multivariate time series. We extend the multi-VAR framework to allow for data-driven identification and penalized estimation of subgroup-specific dynamics. arxiv.org/abs/2409.03085
Interest in the study and analysis of dynamic processes in the social, behavioral, and health sciences has burgeoned in recent years due to the increased availability of intensive longitudinal...
We're hiring a tenure track Quantitative Psychologist at University of North Carolina - Chapel Hill! We are particularly (but not exclusively) seeking someone with expertise in the measurement and modeling of high-density data structures. unc.peopleadmin.com/postings/288222 Please share widely.
Come join me for a couple of workshops the week of June 10! Focusing on Time Series basics and GIMME. Also check out the other workshops available here - so many good ones!
Here is your regular service announcement that making data analyses reproducible is hard (mostly because your past self doesn't reply to emails). Here is our suggestion how to make your R scripts reproducible for your future self and others: www.mdpi.com/2624-8611/3/...
Registration for the first ever Asian school on network psychometrics is now open! @adelaisvoranu.bsky.socialfass.nus.edu.sg/psy/network-...
Enter the dynamic network/GIMME multiverse: ❓What happens when we slightly change (mostly arbitrary) modeling parameters? ❗(Sub-)group results remain robust, individual results may differ more strongly ➡️Use multiverse to explore robustness of data-driven time series modeling techniques osf.io/etm3u
Here is a recent document on likelihood computations for multivariate ordinal probit models (ordinal structural equation models), written so that future me remembers how it works. Topics include quadrature, importance sampling, truncated MVN, and information criteria.
Submissions now OPEN for the 2024 APS Annual Convention! Submit poster, flash talk, and symposium proposals to be presented at APS 2024 by December 20. aps2024.org#PsychSciSky
The effect size and confidence interval guide has now been reformatted into a Quarto book. This guide contains all the equations and code you will need to compute effect sizes and their confidence intervals. It will be constantly updated and maintained! #stats
