论文标题
公正的统计方法如何导致科学发现偏见：应用于伽马射线爆发的光度 - 红外变化的EFRON-Petrosian统计量的案例研究
How unbiased statistical methods lead to biased scientific discoveries: A case study of the Efron-Petrosian statistic applied to the luminosity-redshift evolution of Gamma-Ray Bursts
论文作者
论文摘要
统计方法经常建立在将其适用性限制在某些问题和条件下的假设上。无法识别这些局限性可能导致可能不准确或有偏见的结论。这种方法的一个例子是用于截短数据研究的非参数EFRON-Petrosian检验统计量。我们争论并展示了这种统计方法的不当使用如何导致结论有偏见的结论，而该方法的假设不存在。我们这样做是通过重新研究了有关宇宙学长期长期伽马射线爆发（LGRB）的亮度/能量分布的多个独立报道最近提供的证据。我们表明，在以前的大多数研究中，检测阈值的影响可能被显着低估了。对检测阈值的这种低估导致严重分配的LGRB样品，这些样品表现出强烈的明显光度 - 红外或能量 - 红移相关性。我们通过对LGRB的宇宙速率和光度/能量分布及其检测过程进行广泛的蒙特卡洛模拟，进一步确认我们的发现。
Statistical methods are frequently built upon assumptions that limit their applicability to certain problems and conditions. Failure to recognize these limitations can lead to conclusions that may be inaccurate or biased. An example of such methods is the non-parametric Efron-Petrosian test statistic used in the studies of truncated data. We argue and show how the inappropriate use of this statistical method can lead to biased conclusions when the assumptions under which the method is valid do not hold. We do so by reinvestigating the evidence recently provided by multiple independent reports on the evolution of the luminosity/energetics distribution of cosmological Long-duration Gamma-Ray Bursts (LGRBs) with redshift. We show that the effects of detection threshold has been likely significantly underestimated in the majority of previous studies. This underestimation of detection threshold leads to severely-incomplete LGRB samples that exhibit strong apparent luminosity-redshift or energetics-redshift correlations. We further confirm our findings by performing extensive Monte Carlo simulations of the cosmic rates and the luminosity/energy distributions of LGRBs and their detection process.
