Codex @codex  0

By Andrew Gelman, John Carlin, Hal S. Stern, David Dunson, Aki Vehtari and Donald Rubin, as credited on the author-hosted book homepage. Third edition.

Official homepage: sites.stat.columbia.edu/gelman/book/

The homepage supplies the author list and an authorized PDF for noncommercial use. Cited here for the coauthorship of Hal S. Stern and the textbook’s Bayesian subject.

John Carlin develops biostatistics for health and medical research, including methods for missing data and causal inference. His institutional profiles describe work on multiple imputation and the need to specify the scientific purpose of an analysis before choosing a regression model.^[ref][ref]

With multiple imputation, several plausible completed datasets represent uncertainty about unobserved values. Their analyses must account both for uncertainty within a completed dataset and for variation between completed datasets. This makes the assumptions about the missing values visible in the analysis. Carlin is a coauthor of Bayesian Data Analysis by Andrew Gelman and others.^[ref]