{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T06:35:12Z","timestamp":1772260512543,"version":"3.50.1"},"reference-count":50,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2008,7,1]],"date-time":"2008-07-01T00:00:00Z","timestamp":1214870400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Perspect Psychol Sci"],"published-print":{"date-parts":[[2008,7]]},"abstract":"<jats:p> Replication is fundamental to science, so statistical analysis should give information about replication. Because p values dominate statistical analysis in psychology, it is important to ask what p says about replication. The answer to this question is \u201cSurprisingly little.\u201d In one simulation of 25 repetitions of a typical experiment, p varied from &lt;.001 to .76, thus illustrating that p is a very unreliable measure. This article shows that, if an initial experiment results in two-tailed p = .05, there is an 80% chance the one-tailed p value from a replication will fall in the interval (.00008, .44), a 10% chance that p &lt;.00008, and fully a 10% chance that p &gt;.44. Remarkably, the interval\u2014termed a p interval\u2014is this wide however large the sample size. p is so unreliable and gives such dramatically vague information that it is a poor basis for inference. Confidence intervals, however, give much better information about replication. Researchers should minimize the role of p by using confidence intervals and model-fitting techniques and by adopting meta-analytic thinking. <\/jats:p>","DOI":"10.1111\/j.1745-6924.2008.00079.x","type":"journal-article","created":{"date-parts":[[2008,7,9]],"date-time":"2008-07-09T07:37:59Z","timestamp":1215589079000},"page":"286-300","source":"Crossref","is-referenced-by-count":313,"title":["Replication and <i>p<\/i> Intervals: <i>p<\/i> Values Predict the Future Only Vaguely, but Confidence Intervals Do Much Better"],"prefix":"10.1177","volume":"3","author":[{"given":"Geoff","family":"Cumming","sequence":"first","affiliation":[{"name":"School of Psychological Science, La Trobe University, Melbourne, Victoria, Australia"}]}],"member":"179","published-online":{"date-parts":[[2008,7,1]]},"reference":[{"key":"bibr1-j.1745-6924.2008.00079.x","volume-title":"Statistics as principled argument","author":"Abelson R.P.","year":"1995"},{"key":"bibr2-j.1745-6924.2008.00079.x","volume-title":"Publication manual of the American Psychological Association","author":"American Psychological Association","year":"2001","edition":"5"},{"key":"bibr3-j.1745-6924.2008.00079.x","first-page":"112","volume":"82","author":"Berger J.O.","year":"1987","journal-title":"Journal of the American Statistical Association"},{"key":"bibr4-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1037\/0003-066X.49.12.997"},{"key":"bibr5-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9280.2005.01650.x"},{"key":"bibr6-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9639.2007.00267.x"},{"key":"bibr7-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9280.2007.01881.x"},{"key":"bibr8-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1177\/0013164401614002"},{"key":"bibr9-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1037\/0003-066X.60.2.170"},{"key":"bibr10-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1037\/1082-989X.11.3.217"},{"key":"bibr11-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1207\/s15328031us0304_5"},{"key":"bibr12-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.3758\/BF03208815"},{"key":"bibr13-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.3758\/BF03210790"},{"key":"bibr14-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1111\/j.1523-1739.2006.00525.x"},{"key":"bibr15-j.1745-6924.2008.00079.x","first-page":"1","volume-title":"Best practices in quantitative methods","author":"Fidler F.","year":"2007"},{"key":"bibr16-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1016\/j.socec.2004.09.035"},{"key":"bibr17-j.1745-6924.2008.00079.x","volume-title":"Statistical methods and scientific inference","author":"Fisher R.A.","year":"1959","edition":"2"},{"key":"bibr18-j.1745-6924.2008.00079.x","volume-title":"The design of experiments","author":"Fisher R.A.","year":"1966","edition":"8"},{"key":"bibr19-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1016\/j.socec.2004.09.033"},{"key":"bibr20-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780110705"},{"key":"bibr21-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1097\/00001648-200105000-00006"},{"key":"bibr22-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.2105\/AJPH.78.12.1568"},{"key":"bibr23-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-8986.1996.tb02121.x"},{"key":"bibr24-j.1745-6924.2008.00079.x","first-page":"1","volume":"7","author":"Haller H.","year":"2002","journal-title":"Methods of Psychological Research"},{"key":"bibr25-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.1177\/0959354304043638"},{"key":"bibr26-j.1745-6924.2008.00079.x","doi-asserted-by":"publisher","DOI":"10.2307\/2533093"},{"key":"bibr27-j.1745-6924.2008.00079.x","volume-title":"Methods of meta-analysis. 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