![]() 005 to combat the misinterpretation that is happening in medical literature. ![]() proposed a universal protocol change, moving statistical significance from a p-value of. To avoid perpetrating this form of data fraud (and reduce positive-results bias to boot), some journals and funding organizations are now requiring researchers to preregister their clinical trials, stating in advance what hypotheses they are going to be testing.Background: Misinterpretation of p-values in RCTs is extremely problematic since they are the core basis for high levels of recommendation in clinical practice guidelines, especially Orthopaedics. The lesson here is this: beware of so-called “statistically significant” results. Such ex post results, however, are often just spurious correlations. In the words of Wikipedia: “The process of data dredging involves automatically testing huge numbers of hypotheses about a single data set by exhaustively searching … for combinations of variables that might show a correlation ….” This form of data fraud thus occurs when researchers perform multiple statistical tests on a single set of data and then selectively publish only those results that satisfy some test of statistical significance. Let’s proceed with our parade of fraudulent data practices, shall we? Next up is data dredging (a/k/a “p-hacking”), a more sophisticated (and less transparent) form of cherry picking.
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