How and why alpha should depend on sample size: A Bayesian-frequentist compromise for significance testing Article Swipe

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YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.31234/osf.io/3cbh7

The use of fixed alpha levels in statistical testing is prevalent in management research, but can lead to Lindley's paradox in highly powered studies. In this article, we propose a sample size-adjusted alpha level approach that combines the benefits of both frequentist and Bayesian statistics, enabling strict hypothesis testing with known error rates while also quantifying the evidence for a hypothesis. We present an R-package that can be used to set the sample size-adjusted alpha level for generalized linear models, including linear regression, logistic regression, and Poisson regression. This approach can help researchers stop relying on mindless defaults and avoid situations where they reject the null hypothesis when the evidence in the test actually favors the null hypothesis, improving the accuracy and robustness of statistical analysis in management research.

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Frequentist inference Null hypothesis Statistical hypothesis testing Econometrics Bayesian probability Statistics Sample size determination Robustness (evolution) Frequentist probability Computer science Mathematics Bayesian inference Chemistry Gene Biochemistry

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Type: preprint
Language: en
Landing Page: https://doi.org/10.31234/osf.io/3cbh7
PDF: https://psyarxiv.com/3cbh7/download
OA Status: gold
Cited By: 5
References: 96
Related Works: 10
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DOI: https://doi.org/10.31234/osf.io/3cbh7

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Title: How and why alpha should depend on sample size: A Bayesian-frequentist compromise for significance testing

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Type: preprint

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Language: en

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Publication year: 2023

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Publication date: 2023-01-05

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Authors: Jesper Wulff, Luke Taylor

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Landing page: https://doi.org/10.31234/osf.io/3cbh7

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PDF URL: https://psyarxiv.com/3cbh7/download

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Concepts: Frequentist inference, Null hypothesis, Statistical hypothesis testing, Econometrics, Bayesian probability, Statistics, Sample size determination, Robustness (evolution), Frequentist probability, Computer science, Mathematics, Bayesian inference, Chemistry, Gene, Biochemistry

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Cited by: 5

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abstract_inverted_index.reject	103
abstract_inverted_index.sample	30, 72
abstract_inverted_index.strict	46
abstract_inverted_index.Poisson	86
abstract_inverted_index.models,	79
abstract_inverted_index.paradox	19
abstract_inverted_index.powered	22
abstract_inverted_index.present	62
abstract_inverted_index.propose	28
abstract_inverted_index.relying	94
abstract_inverted_index.testing	8, 48
abstract_inverted_index.Bayesian	43
abstract_inverted_index.accuracy	120
abstract_inverted_index.actually	113
abstract_inverted_index.analysis	125
abstract_inverted_index.approach	34, 89
abstract_inverted_index.article,	26
abstract_inverted_index.benefits	38
abstract_inverted_index.combines	36
abstract_inverted_index.defaults	97
abstract_inverted_index.enabling	45
abstract_inverted_index.evidence	57, 109
abstract_inverted_index.logistic	83
abstract_inverted_index.mindless	96
abstract_inverted_index.studies.	23
abstract_inverted_index.Lindley's	18
abstract_inverted_index.R-package	64
abstract_inverted_index.improving	118
abstract_inverted_index.including	80
abstract_inverted_index.prevalent	10
abstract_inverted_index.research,	13
abstract_inverted_index.research.	128
abstract_inverted_index.hypothesis	47, 106
abstract_inverted_index.management	12, 127
abstract_inverted_index.robustness	122
abstract_inverted_index.situations	100
abstract_inverted_index.frequentist	41
abstract_inverted_index.generalized	77
abstract_inverted_index.hypothesis,	117
abstract_inverted_index.hypothesis.	60
abstract_inverted_index.quantifying	55
abstract_inverted_index.regression,	82, 84
abstract_inverted_index.regression.	87
abstract_inverted_index.researchers	92
abstract_inverted_index.statistical	7, 124
abstract_inverted_index.statistics,	44
abstract_inverted_index.size-adjusted	31, 73
cited_by_percentile_year.max	97
cited_by_percentile_year.min	89
countries_distinct_count	1
institutions_distinct_count	2
citation_normalized_percentile.value	0.86179355
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	True