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排卵估计方法的有效性及其对与排卵相关的行为波动进行统计检测的影响。

Efficacy of methods for ovulation estimation and their effect on the statistical detection of ovulation-linked behavioral fluctuations.

作者信息

Gonzales Joseph E, Ferrer Emilio

机构信息

Department of Psychology, University of California, Davis, One Shields Ave., Davis, CA, 95616-8686, USA.

出版信息

Behav Res Methods. 2016 Sep;48(3):1125-44. doi: 10.3758/s13428-015-0638-4.

Abstract

Contention of the ovulatory shift hypothesis is principally supported by failures to replicate previous findings; e.g., recent meta-analytic work suggests that the effects endorsing the hypothesis may not be robust. Some possible limitations in this and other ovulatory-effects research-that may contribute to such controversy arising-are: (a) use of error-prone methods for assessing target periods of fertility that are thought to be associated with behavioral shifts, and (b) use of between-subjects-as opposed to within-subjects-methods. In the current study we present both simulated and empirical research: (a) comparing the ability of between- and within-subject t-tests to detect cyclical shifts; (b) evaluating the efficacy of correlating estimated fertility overlays with potential behavioral shifts; and (c) testing the accuracy of counting methods for identifying windows of cycle fertility. While this study cannot assess whether the ovulatory shift hypothesis or other ovulatory-based hypotheses are tenable, it demonstrates how low power resulting from typical methods employed in the extant literature may be associated with perceived inconsistencies in findings. We conclude that to fully address this issue greater use of within-subjects methodology is needed.

摘要

排卵转变假说的论点主要是由于无法重复先前的研究结果而得到支持;例如,最近的荟萃分析工作表明,支持该假说的效应可能并不稳健。这一研究以及其他排卵效应研究中一些可能导致此类争议产生的局限性包括:(a) 使用容易出错的方法来评估被认为与行为转变相关的生育目标期,以及(b) 使用组间方法而非组内方法。在当前研究中,我们展示了模拟研究和实证研究:(a) 比较组间和组内t检验检测周期性转变的能力;(b) 评估估计的生育叠加与潜在行为转变之间的相关性的功效;以及(c) 测试识别周期生育窗口的计数方法的准确性。虽然本研究无法评估排卵转变假说或其他基于排卵的假说是否成立,但它表明了现有文献中常用方法导致的低效能可能与研究结果中明显的不一致性有关。我们得出结论,要全面解决这个问题,需要更多地使用组内方法。

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