P-Value Precision and Reproducibility

P-values are useful statistical measures of evidence against a null hypothesis. In contrast to other statistical estimates, however, their sample-to-sample variability is usually not considered or estimated, and therefore not fully appreciated. Via a systematic study of log-scale p-value standard er...

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Vydané v:	The American statistician Ročník 65; číslo 4; s. 213 - 221
Hlavní autori:	Boos, Dennis D., Stefanski, Leonard A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Alexandria, VA Taylor & Francis 01.11.2011 American Statistical Association
Predmet:	Approximation Bootstrap method Errors Exact sciences and technology General topics Hypothesis testing Inference from stochastic processes; time series analysis Log p-value Mathematics Measure of evidence Null hypothesis P values Parametric inference Prediction interval Probabilities Probability and statistics Probability theory and stochastic processes Random sampling Reproducibility Reproducibility probability Sample size Sampling distributions Sciences and techniques of general use Standard deviation Standard error Statistical significance Statistical variance Statistics Stochastic processes Values Variability Statistical contrast Log p-value Error estimation Reproducibility probability Prediction Probability Prediction theory Statistical estimation Probability distribution Stochastic process Prediction interval Measure of evidence Hypothesis test Bootstrap Jackknife method Filtering theory P value Resampling method
ISSN:	0003-1305, 1537-2731
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Popis
Shrnutí:	P-values are useful statistical measures of evidence against a null hypothesis. In contrast to other statistical estimates, however, their sample-to-sample variability is usually not considered or estimated, and therefore not fully appreciated. Via a systematic study of log-scale p-value standard errors, bootstrap prediction bounds, and reproducibility probabilities for future replicate p-values, we show that p-values exhibit surprisingly large variability in typical data situations. In addition to providing context to discussions about the failure of statistical results to replicate, our findings shed light on the relative value of exact p-values vis-a-vis approximate p-values, and indicate that the use of , , and ** to denote levels 0.05, 0.01, and 0.001 of statistical significance in subject-matter journals is about the right level of precision for reporting p-values when judged by widely accepted rules for rounding statistical estimates.
Bibliografia:	SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
ISSN:	0003-1305 1537-2731
DOI:	10.1198/tas.2011.10129