G2TT
来源类型Discussion paper
规范类型论文
来源IDDP16942
DP16942 Incentive-Compatible Critical Values
Pascal Michaillat; Adam McCloskey
发表日期2022-01-21
出版年2022
语种英语
摘要Statistically significant results are more rewarded than insignificant ones, so researchers have the incentive to pursue statistical significance. Such p-hacking reduces the informativeness of hypothesis tests by making significant results much more common than they are supposed to be in the absence of true significance. To address this problem, we construct critical values of test statistics such that, if these values are used to determine significance, and if researchers optimally respond to these new significance standards, then significant results occur with the desired frequency. Such incentive-compatible critical values allow for p-hacking so they are larger than classical critical values. Using evidence from the social and medical sciences, we find that the incentive-compatible critical value for any test and any significance level is the classical critical value for the same test with approximately one fifth of the significance level—a form of Bonferroni correction. For instance, for a z-test with a significance level of 5%, the incentive-compatible critical value is 2.31 instead of 1.65 if the test is one-sided and 2.57 instead of 1.96 if the test is two-sided.
主题Labour Economics ; Public Economics
关键词Hypothesis testing Academic incentives P-hacking Statistical significance Optimal stopping
URLhttps://cepr.org/publications/dp16942
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/545882
推荐引用方式
GB/T 7714
Pascal Michaillat,Adam McCloskey. DP16942 Incentive-Compatible Critical Values. 2022.
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