These problems are not unique to the study of cGxE (J.P. Ioannidis et al., 2014; Spellman, 2012). Concern about unacceptably high false positive rates in the social sciences has garnered growing attention over the past several years. In a provocative paper by Iaonnidis (J. P. Ioannidis, 2005) entitled “Why Most Published Research Findings are False,” a number of conditions are outlined that contribute to why a novel research finding ultimately may be in error. These conditions include smaller studies; smaller effect sizes; greater number and lesser preselection of tested relationships; greater flexibility in designs, definitions, outcomes, and analytic models; greater interests and prejudices surrounding the area of research; and situations in which there are more scientists in a field involved in chase of statistical significance. We believe that all of these conditions are likely to contribute to findings in the study of cGxE.
