babebi: An R Package for Bayesian Estimation and Validation in Small-N Two-Rater Pre–Post Designs

babebi is an R package for analysing complete two-time, two-rater pre–post rating designs. The package estimates pre–post effects using a linear model with a rater indicator as covariate and provides adjusted estimates of change, posterior summaries, and BIC-based Bayes factor approximations. It also includes Monte Carlo validation routines calibrated from the observed design to evaluate inferential performance under study-specific conditions.

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Publication Details

Journal
Applied Psychological Measurement
Published
2026-06-30
DOI
https://doi.org/10.1177/01466216261465754
Primary Topic
Psychometric Methodologies and Testing
Type
article
Field-Weighted Citation Impact
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article

babebi: An R Package for Bayesian Estimation and Validation in Small-N Two-Rater Pre–Post Designs

Demis Basso, Andrea Bosco, Irene Gianeselli
Applied Psychological Measurement
Psychometric Methodologies and Testing
article

babebi: An R Package for Bayesian Estimation and Validation in Small-N Two-Rater Pre–Post Designs

Demis Basso, Andrea Bosco, Irene Gianeselli
article en

Abstract

babebi is an R package for analysing complete two-time, two-rater pre–post rating designs. The package estimates pre–post effects using a linear model with a rater indicator as covariate and provides adjusted estimates of change, posterior summaries, and BIC-based Bayes factor approximations. It also includes Monte Carlo validation routines calibrated from the observed design to evaluate inferential performance under study-specific conditions.

Applied Psychological Measurement
Free University of Bozen-Bolzano (IT), University of Bari Aldo Moro (IT)
Openalex Percentile: Top 4%
Psychometric Methodologies and Testing
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