Abstract
Summary
There
is increasing concern that most current published research findings are
false. The probability that a research claim is true may depend on
study power and bias, the number of other studies on the same question,
and, importantly, the ratio of true to no relationships among the
relationships probed in each scientific field. In this framework, a
research finding is less likely to be true when the studies conducted in
a field are smaller; when effect sizes are smaller; when there is a
greater number and lesser preselection of tested relationships; where
there is greater flexibility in designs, definitions, outcomes, and
analytical modes; when there is greater financial and other interest and
prejudice; and when more teams are involved in a scientific field in
chase of statistical significance. Simulations show that for most study
designs and settings, it is more likely for a research claim to be false
than true. Moreover, for many current scientific fields, claimed
research findings may often be simply accurate measures of the
prevailing bias. In this essay, I discuss the implications of these
problems for the conduct and interpretation of research.
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