Replication and <i>p</i> Intervals: <i>p</i> Values Predict the Future Only Vaguely, but Confidence Intervals Do Much Better Export

@article{citeulike:2998323, abstract = {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 ” Surprisingly little.” In one simulation of 25 repetitions of a typical experiment, p varied from <.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 < .00008, and fully a 10\% chance that p > .44. Remarkably, the interval—termed a p interval—is 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.}, address = {School of Psychological Science, La Trobe University, Melbourne, Victoria, Australia}, author = {Cumming, Geoff}, citeulike-article-id = {2998323}, citeulike-linkout-0 = {http://dx.doi.org/10.1111/j.1745-6924.2008.00079.x}, citeulike-linkout-1 = {http://www.ingentaconnect.com/content/bsc/ppsc/2008/00000003/00000004/art00003}, citeulike-linkout-2 = {http://www3.interscience.wiley.com/cgi-bin/abstract/120736945/ABSTRACT}, doi = {10.1111/j.1745-6924.2008.00079.x}, issn = {1745-6924}, journal = {Perspectives on Psychological Science}, keywords = {methodology, statistics}, month = {July}, number = {4}, pages = {286--300}, posted-at = {2008-10-21 22:52:30}, priority = {2}, publisher = {Blackwell Publishing}, title = {Replication and <i>p</i> Intervals: <i>p</i> Values Predict the Future Only Vaguely, but Confidence Intervals Do Much Better}, url = {http://dx.doi.org/10.1111/j.1745-6924.2008.00079.x}, volume = {3}, year = {2008} }

TY - JOUR ID - citeulike:2998323 L3 - citeulike-article-id:2998323 N2 - 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 “Surprisingly little.” In one simulation of 25 repetitions of a typical experiment, p varied from <.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 < .00008, and fully a 10% chance that p > .44. Remarkably, the interval—termed a p interval—is 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. IS - 4 JF - Perspectives on Psychological Science SN - 1745-6924 AD - School of Psychological Science, La Trobe University, Melbourne, Victoria, Australia EP - 300 TI - Replication and <i>p</i> Intervals: <i>p</i> Values Predict the Future Only Vaguely, but Confidence Intervals Do Much Better PB - Blackwell Publishing VL - 3 SP - 286 KW - methodology KW - statistics AU - Cumming, Geoff PY - 2008/07// UR - http://dx.doi.org/10.1111/j.1745-6924.2008.00079.x ER -