= John Carlin
{c}
<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>.https://www.vicbiostat.org.au/people/john-carlin[Research interests, imputation and scientific practice]{ref}https://www.mcri.edu.au/researcher-details/john-carlin[Methodological research and applications]{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>.<Bayesian Data Analysis by Andrew Gelman and others>[Third-edition author list and missing-data methods]{ref}
\Image[https://www.mcri.edu.au/images/profiles/john-carlin.jpeg]
{title=John Carlin}
{description=Portrait identified on the linked official researcher profile; photographer and licence are not asserted.}
{source=https://www.mcri.edu.au/researcher-details/john-carlin}
{width=220}
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