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多变量概率单位分析:医学统计学中一个被忽视的方法。

Multivariate probit analysis: a neglected procedure in medical statistics.

作者信息

Lesaffre E, Molenberghs G

机构信息

Biostatistical Centre, Department of Epidemiology, Leuven, Belgium.

出版信息

Stat Med. 1991 Sep;10(9):1391-403. doi: 10.1002/sim.4780100907.

Abstract

The multivariate probit model is designed to regress a vector of correlated quantal variables on a mixture of continuous and discrete predictors. Various applications can be found in the biological, economical and psychosociological literature, but the method is not yet widely used in medical applications. We reintroduce this model thereby showing its usefulness in medical problems. Software for this model is, however, not widely available. We have written a PC program to select predictors and estimate parameters in the multivariate probit framework. The performance and characteristics of the program are briefly illustrated.

摘要

多变量概率单位模型旨在将一组相关的定量变量对连续和离散预测变量的混合进行回归。在生物学、经济学和心理社会学文献中可以找到各种应用,但该方法在医学应用中尚未得到广泛使用。我们重新引入此模型,从而展示其在医学问题中的有用性。然而,该模型的软件并不广泛可用。我们编写了一个PC程序,用于在多变量概率单位框架中选择预测变量并估计参数。简要说明了该程序的性能和特点。

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