Missing Observations in Multivariate Statistics I. Review of the Literature
Missing Observations in Multivariate Statistics I. Review of the Literature
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DOI：
10.1080/01621459.1966.10480891
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发表时间：
1966-09
影响因子：
3.7
通讯作者：
A. Afifi;R. Elashoff
中科院分区：
文献类型：
--
作者：
A. Afifi;R. Elashoff
摘要：本文综述了关于在部分或全部研究变量上缺失观测值的多变量数据处理问题的文献。我们研究了统计学家从这些数据中估计均值、方差、相关性和线性回归函数的方法，并参考了执行估计的特定计算机程序。我们展示了如果缺失的数据遵循某些模式，如何简化估计问题。最后，我们概述了各种估计量的统计性质。
Abstract In this paper we review the literature on the problem of handling multivariate data with observations missing on some or all of the variables under study. We examine the ways that statisticians have devised to estimate means, variances, correlations and linear regression functions from such data and refer to specific computer programs for carrying out the estimation. We show how the estimation problems can be simplified if the missing data follows certain patterns. Finally, we outline the statistical properties of the various estimators.