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Faktoriális kísérleti elrendezés kereszteződéssel×Latin négyzet és görög-latin négyzet elrendezés×
TudományterületKísérlettervezésKísérlettervezés
MódszercsaládProcess / pipelineHypothesis test
Keletkezés éve1920s–1960s (synthesis of factorial and crossover traditions)1935
MegalkotóR. A. Fisher (factorial principles, 1920s); crossover integration developed in biostatistics through mid-20th centuryRonald A. Fisher
TípusExperimental designParametric blocked ANOVA
AlapműJones, B., & Kenward, M. G. (2014). Design and Analysis of Cross-Over Trials (3rd ed.). Chapman and Hall/CRC. ISBN: 978-1439861424Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443
Alternatív nevekwithin-subject factorial design, repeated-measures factorial experiment, factorial crossover trial, crossover factorial trialLatin Square, Greco-Latin Square, Latin Kare ve Greco-Latin Kare Deseni
Kapcsolódó55
ÖsszefoglalóA crossover factorial experiment combines two powerful design principles: factorial structure, which studies multiple factors and their interactions simultaneously, and crossover structure, in which each participant receives more than one treatment combination across sequential periods. By serving as their own control, participants reduce between-subject variability, improving statistical power while also revealing how different factor levels interact within the same individual.The Latin square design is a blocked experimental design that simultaneously controls two independent nuisance factors — the row block and the column block — so that each treatment appears exactly once in every row and every column of an n×n arrangement. Formalised by Ronald A. Fisher in his 1935 monograph The Design of Experiments, the design dramatically reduces experimental error by absorbing variation from two extraneous sources before the treatment effects are estimated.
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ScholarGateMódszerek összehasonlítása: Crossover Factorial Experiment · Latin Square Design. Letöltve 2026-06-19, forrás: https://scholargate.app/hu/compare