Performing Contrast Analysis in Factorial Designs: From NHST to Confidence Intervals and Beyond

Autor/inn/en	Wiens, Stefan; Nilsson, Mats E.
Titel	Performing Contrast Analysis in Factorial Designs: From NHST to Confidence Intervals and Beyond
Quelle	In: Educational and Psychological Measurement, 77 (2017) 4, S.690-715 (26 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164416668950
Schlagwörter	Data Analysis; Effect Size; Computation; Statistical Analysis; Bayesian Statistics; Hypothesis Testing + Suchen Sie Ihr Suchwort? Auswertung; Statistische Analyse; Hypothesenprüfung; Hypothesentest
Abstract	Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs). However, researchers may be unsure about how to extract effect sizes from factorial designs. Contrast analysis is helpful because it can be used to test specific questions of central interest in studies with factorial designs. It weighs several means and combines them into one or two sets that can be tested with t tests. The effect size produced by a contrast analysis is simply the difference between means. The CI of the effect size informs directly about direction, hypothesis exclusion, and the relevance of the effects of interest. However, any interpretation in terms of precision or likelihood requires the use of likelihood intervals or credible intervals (Bayesian). These various intervals and even a Bayesian t test can be obtained easily with free software. This tutorial reviews these methods to guide researchers in answering the following questions: When I analyze mean differences in factorial designs, where can I find the effects of central interest, and what can I learn about their effect sizes? (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01