An introduction to Bayesian hypothesis testing for management research
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
ID 3351532
Author(s) Andraszewicz, S.; Scheibehenne, B.; Rieskamp, J.; Grasman, R.; Verhagen, J.; Wagenmakers, E. J.
Author(s) at UniBasel Rieskamp, Jörg
Year 2015
Title An introduction to Bayesian hypothesis testing for management research
Journal Journal of Management
Volume 41
Number 2
Pages / Article-Number 521-543
Keywords bayes factor; statistical evidence; optional stopping; model selection; p-values; statistical-inference; psychological science; editors introduction; variable selection; prior sensitivity; null hypotheses; social-research; isnt everyone
Abstract In management research, empirical data are often analyzed using p-value null hypothesis significance testing (pNHST). Here we outline the conceptual and practical advantages of an alternative analysis method: Bayesian hypothesis testing and model selection using the Bayes factor. In contrast to pNHST, Bayes factors allow researchers to quantify evidence in favor of the null hypothesis. Also, Bayes factors do not require adjustment for the intention with which the data were collected. The use of Bayes factors is demonstrated through an extended example for hierarchical regression based on the design of an experiment recently published in the Journal of Management. This example also highlights the fact that p values overestimate the evidence against the null hypothesis, misleading researchers into believing that their findings are more reliable than is warranted by the data.
Publisher Sage Publications
ISSN/ISBN 0149-2063 ; 1557-1211
Full Text on edoc No
Digital Object Identifier DOI 10.1177/0149206314560412
ISI-Number 000348530700007
Document type (ISI) Article

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