Are Inconsistencies among Studies due to False-Positives or False-Negatives?
It is possible that type 1 error could contribute to false-positive results, i.e., even in the absence of a true genotype-phenotype association, 1 in 20 studies will show a statistically significant result at the p < 0.05 level of statistical significance by chance alone. Moreover, as the number of comparisons within any particular study increases, the probability of a significant result on any one test increases by chance alone. To minimize this possibility, some studies use the Bonferroni adjustment or similar corrections, although such procedures may be an overcorrection and lead to inflated type 2 error rates because the tested phenotypes tend to be correlated with each other. Others still would argue that Bonferroni's correction is too conservative for hypothesis-driven investigations; for example, when there is a priori evidence for a genotype–phenotype association. Another source of potential confounding is publication bias. Positive studies are more likely to be published than
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