Joseph Bulbulia @joseph_bulbulia@qoto.org

Fantastic paper describes the bias that may arise *from* #regularisation in a multi level model.

https://www.cambridge.org/core/journals/political-analysis/article/understanding-choosing-and-unifying-multilevel-and-fixed-effect-approaches/8101D49CFD3B129F5753FC878F416980

Simple correction the authors propose only works if there is *no* treatment-confounder feedback(see: https://go-bayes.github.io/b-causal/posts/confounder-treatment-feedback/conf-out-feedback.html)

#causalinference #statsdon

@f2harrell has a great post on the problems with changes scores:

http://hbiostat.org/bbr/change.html#sec-changegen

#introduction

Hi,

I'm Joseph Bulbulia (Joe).

I teach #QuantitativePsychology at Victoria University of Wellington.

I serve on the leadership team of the New Zealand Attitudes and Values Study.

I supervise graduate students interested in #longitudinal methods for national-scale #paneldata.

My substantive research interests are in the psychology of religion, cultural evolution, moral psychology, well-being, and more recently #climatepsychology.

Big fan of the #potentialoutcomes framework for #causalinference.

Not a big fan of #prediction and #associations in #psychology.

I migrated to qoto.org because of its nice interface and science community.*

-- Joe

*Also, I think I can write things like

\[E(Y^1) - E(Y^0) \neq 0\]