University of Heidelberg, Germany.
Perspect Psychol Sci. 2017 Jan;12(1):46-61. doi: 10.1177/1745691616654458.
A Bayesian perspective on Ioannidis's (2005) memorable statement that "Most Published Research Findings Are False" suggests a seemingly inescapable trade-off: It appears as if research hypotheses are based either on safe ground (high prior odds), yielding valid but unsurprising results, or on unexpected and novel ideas (low prior odds), inspiring risky and surprising findings that are inevitably often wrong. Indeed, research of two prominent types, sexy hypothesis testing and model testing, is often characterized by low priors (due to astounding hypotheses and conjunctive models) as well as low-likelihood ratios (due to nondiagnostic predictions of the yin-or-yang type). However, the trade-off is not inescapable: An alternative research approach, theory-driven cumulative science, aims at maximizing both prior odds and diagnostic hypothesis testing. The final discussion emphasizes the value of pluralistic science, within which exploratory phenomenon-driven research can play a similarly strong part as strict theory-testing science.
贝叶斯视角下的约安尼季斯(Ioannidis)2005 年令人难忘的言论“大多数已发表的研究结果都是错误的”表明存在一种看似不可避免的权衡:研究假设似乎要么基于安全基础(高先验概率),得出有效但不足为奇的结果,要么基于出乎意料和新颖的想法(低先验概率),从而产生风险大且令人惊讶的结果,而这些结果往往不可避免地是错误的。实际上,两种突出类型的研究——性感假设检验和模型检验,通常具有低先验概率(由于惊人的假设和联合模型)和低似然比(由于阴阳类型的非诊断性预测)。然而,这种权衡并非不可避免:一种替代的研究方法,即理论驱动的累积科学,旨在最大化先验概率和诊断假设检验。最后的讨论强调了多元科学的价值,其中探索性现象驱动的研究可以与严格的理论检验科学一样发挥强大的作用。