BIVARIATE MEDIAN SPLITS AND SPURIOUS STATISTICAL SIGNIFICANCE
BIVARIATE MEDIAN SPLITS AND SPURIOUS STATISTICAL SIGNIFICANCE
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DOI：
10.1037/0033-2909.113.1.181
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发表时间：
1993-01-01
影响因子：
22.4
通讯作者：
DELANEY, HD
中科院分区：
文献类型：
--
作者：
MAXWELL, SE;DELANEY, HD
尽管方法学家提出了请求，但研究人员经常继续对连续预测变量进行二分法。反对这种做法的主要论点是，它低估了关系的强度，降低了统计能力。虽然这个论点对于涉及单个预测因子的关系是正确的，但当涉及多个预测因子时，可能会出现不同的问题。具体来说，将2个连续自变量二分可能导致虚假的统计显著性。因此，只要结果继续具有统计学显著性，则使用中位数分割的典型理由是无效的，因为这些结果实际上可能是虚假的。因此，研究人员二分法多个连续的预测变量不仅可能会失去权力，以检测真正的预测标准的关系，在某些情况下，但也可能会大大增加1型错误的概率在其他情况下。
Despite pleas from methodologists, researchers often continue to dichotomize continuous predictor variables. The primary argument against this practice has been that it underestimates the strength of relationships and reduces statistical power. Although this argument is correct for relationships involving a single predictor, a different problem can arise when multiple predictors are involved. Specifically, dichotomizing 2 continuous independent variables can lead to false statistical significance. As a result, the typical justification for using a median split as long as results continue to be statistically significant is invalid, because such results may in fact be spurious. Thus, researchers who dichotomize multiple continuous predictor variables not only may lose power to detect true predictor-criterion relationships in some situations but also may dramatically increase the probability of Type 1 errors in other situations.