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Standardized Regression Coefficients and Newly Proposed Estimators for $${R}^{{2}}$$R2 in Multiply Imputed Data
Psychometrika ( IF 3 ) Pub Date : 2020-03-01 , DOI: 10.1007/s11336-020-09696-4
Joost R van Ginkel 1
Affiliation  

Whenever statistical analyses are applied to multiply imputed datasets, specific formulas are needed to combine the results into one overall analysis, also called combination rules. In the context of regression analysis, combination rules for the unstandardized regression coefficients, the t-tests of the regression coefficients, and the F-tests for testing [Formula: see text] for significance have long been established. However, there is still no general agreement on how to combine the point estimators of [Formula: see text] in multiple regression applied to multiply imputed datasets. Additionally, no combination rules for standardized regression coefficients and their confidence intervals seem to have been developed at all. In the current article, two sets of combination rules for the standardized regression coefficients and their confidence intervals are proposed, and their statistical properties are discussed. Additionally, two improved point estimators of [Formula: see text] in multiply imputed data are proposed, which in their computation use the pooled standardized regression coefficients. Simulations show that the proposed pooled standardized coefficients produce only small bias and that their 95% confidence intervals produce coverage close to the theoretical 95%. Furthermore, the simulations show that the newly proposed pooled estimates for [Formula: see text] are less biased than two earlier proposed pooled estimates.

中文翻译:

乘法插补数据中 $${R}^{{2}}$$R2 的标准化回归系数和新提出的估计量

每当将统计分析应用于多重插补数据集时,都需要特定的公式将结果组合成一个整体分析,也称为组合规则。在回归分析的背景下,非标准化回归系数的组合规则、回归系数的 t 检验以及用于检验显着性的 F 检验 [公式:见正文] 早已建立。然而,对于如何在应用于多重插补数据集的多元回归中组合 [公式:见正文] 的点估计量,仍然没有普遍的共识。此外,似乎根本没有制定标准化回归系数及其置信区间的组合规则。在当前的文章中,提出了两组标准化回归系数及其置信区间的组合规则,并讨论了它们的统计特性。此外,还提出了乘法插补数据中 [公式:见正文] 的两个改进点估计器,它们在计算中使用合并的标准化回归系数。模拟表明,提议的合并标准化系数仅产生很小的偏差,并且它们的 95% 置信区间产生接近理论 95% 的覆盖率。此外,模拟表明,新提出的 [公式:见正文] 的合并估计比两个早先提出的合并估计偏差更小。请参阅文本] 在乘法估算数据中提出,在他们的计算中使用合并的标准化回归系数。模拟表明,提议的合并标准化系数仅产生很小的偏差,并且它们的 95% 置信区间产生接近理论 95% 的覆盖率。此外,模拟表明,新提出的 [公式:见正文] 的合并估计比两个早先提出的合并估计偏差更小。请参阅文本] 在乘法估算数据中提出,在他们的计算中使用合并的标准化回归系数。模拟表明,提议的合并标准化系数仅产生很小的偏差,并且它们的 95% 置信区间产生接近理论 95% 的覆盖率。此外,模拟表明,新提出的 [公式:见正文] 的合并估计比两个早先提出的合并估计偏差更小。
更新日期:2020-03-01
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