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When studies examine true effects, they generate right-skewed p-curves, distributions of statistically significant results with more low (.01 s) than high (.04 s) p values. What else can cause a right-skewed p-curve? First, we consider the possibility that researchers report only the smallest significant p value (as conjectured by Ulrich & Miller, 2015), concluding that it is a very uncommon problem. We then consider more common problems, including (a) p-curvers selecting the wrong p values, (b) fake data, (c) honest errors, and (d) ambitiously p-hacked (beyond p < .05) results. We evaluate the impact of these common problems on the validity of p-curve analysis, and provide practical solutions that substantially increase its robustness.
Link to resource: https://doi.org/10.1037/xge0000104.
Type of resources: Primary Source, Reading, Paper
Education level(s): College / Upper Division (Undergraduates)
Primary user(s): Student
Subject area(s): Applied Science, Math & Statistics, Social Science