High-dimensional multivariate probit analysis.
High-dimensional multivariate probit analysis.
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DOI：
10.2307/2532834
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发表时间：
1996-12
期刊：
影响因子：
1.9
通讯作者：
R. D. Bock;Robert D. Gibbons
中科院分区：
文献类型：
--
作者：
R. D. Bock;Robert D. Gibbons
提出了一种基于假定的潜在容差公因子模型的多响应变量概率分析的实用计算形式。因子空间上的数值积分提供了probit回归参数和模型下响应组合概率的最大似然估计。该程序应用于尘肺病现场试验中的五个变量，其中两个变量先前由Ashford和Sowden （1970, Biometrics 26,535 -546）进行了分析。
A computationally practical form of probit analysis for multiple response variables based on an assumed common factor model for the latent tolerances is proposed. Numerical integration over the factor space provides maximum likelihood estimation of the probit regression parameters and of the probabilities of response combinations under the model. The procedure is applied to five variables from the Pneumoconiosis Field Trial, two variables of which were previously analyzed by Ashford and Sowden (1970, Biometrics 26, 535-546).