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Godina nastanka1964 (Kerlinger ex post facto); Bayesian integration from 1990s–2000s onward1964
TvoracFrederick N. Kerlinger (ex post facto framework); Bayesian extension draws on Laplace and modern Bayesian statisticsFred N. Kerlinger
TipQuantitative observational research design with Bayesian inferenceNon-experimental quantitative research design
Temeljni izvorKerlinger, F. N. (1973). Foundations of Behavioral Research (2nd ed.). Holt, Rinehart and Winston. link ↗Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston. link ↗
Drugi naziviBayesian causal-comparative design, Bayesian after-the-fact design, Bayesian observational causal design, Bayesian retrospective causal studyex post facto research, causal-comparative design, retrospective causal study, CCR
Srodne53
SažetakBayesian 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.Causal-comparative research is a non-experimental quantitative design in which the researcher compares two or more groups that already differ on an independent variable — one that was not manipulated — to investigate possible causes or consequences of that difference. Because group membership is pre-existing rather than randomly assigned, the design can suggest causal relationships but cannot establish them with the certainty of a true experiment. It is widely used in education, psychology, and social sciences when experimental manipulation is impractical or unethical.
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ScholarGateUporedite metode: Bayesian Ex Post Facto Design · Causal-Comparative Research. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare