Data-dredging bias

Background: what is data dredging bias? Data-dredging bias encompasses a number of more specific questionable practices (eg, fishing, p-hacking) all of which involve probing data using unplanned analyses and then reporting salient results without accurately describing the processes by which the results were generated. Almost any process of data analysis involves numerous decisions necessary to complete the analysis (eg, how to handle outliers, whether to combine groups, including/excluding covariates). Where possible, it is the best practice for these decisions to be guided by a principled approach and prespecified in a publicly available protocol. When it is not possible, authors must be transparent about the open-ended nature of their analysis. Many different sets of choices may well be methodologically defensible and reliablewhen the specifications are made prior to the analysis. However, probing the data and selectively reporting an outcome as if it were always the intended course of analysis...
Source: Evidence-Based Medicine - Category: Internal Medicine Authors: Tags: EBM learning Source Type: research