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Multivariační kauzálně-srovnávací výzkum×Diskriminační analýza×
OborDesign výzkumuStatistika
RodinaProcess / pipelineLatent structure
Rok vznikuMid-20th century onward; multivariate extension systematized 1970s–1990s1936
TvůrceExtension of causal-comparative tradition (cf. Chapin, 1947; Gay, Mills & Airasian)Ronald A. Fisher
TypQuantitative non-experimental comparative designSupervised classification and dimension reduction
Původní zdrojFraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to Design and Evaluate Research in Education (10th ed.). McGraw-Hill. ISBN: 978-1260085594Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗
Další názvymultivariate causal-comparative design, MANOVA causal-comparative study, multi-outcome ex post facto research, multivariate ex post facto designLDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
Příbuzné64
ShrnutíMultivariate causal-comparative research is a quantitative, non-experimental design that investigates whether pre-existing group differences (defined by a naturally occurring categorical variable) are associated with differences across multiple outcome variables considered simultaneously. By extending the classic causal-comparative framework to several dependent variables at once, it reduces Type I error inflation and captures the correlated structure of outcomes that univariate comparisons would miss.Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error.
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ScholarGatePorovnat metody: Multivariate Causal-Comparative Research · Discriminant Analysis. Získáno 2026-06-17 z https://scholargate.app/cs/compare