Method evidence record

Bayesian Ex Post Facto Design

Bayesian ex post facto design investigates possible causal relationships among variables that have already occurred, without researcher manipulation of those variables, and quantifies uncertainty about those relationships using Bayesian statistical inference. The researcher selects groups that differ on an outcome or a presumed cause after the fact, then uses prior knowledge and observed data together — via Bayes' theorem — to estimate credible effect sizes, group differences, or predictors.

Evidence statusSources recorded, not reviewedBibliographic sources are present. Claim-level evidence review has not been performed.

Source record

Recorded

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Bayesian Ex Post Facto Research Design

Taxonomic method recordprocess-pipelineresearch-design

  1. Kruschke, J. K. (2015). Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan (2nd ed.). Academic Press. · ISBN 978-0124058880

Open full method2 recorded citations, copied from the method source record.

Curated claims

Assessed

Claims persisted in the evidence ledger, each with its own assessment.

No curated claims yet

This view does not invent a claim assessment when the ledger has none.

Related methods

Suggested5

Generated from the method graph and shown as machine-suggested relations. No evidence claim is inferred.