Bock R D, Gibbons R D
Department of Psychology, University of Chicago, Illinois 60637, USA.
Biometrics. 1996 Dec;52(4):1183-94.
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).
基于潜在耐受性的假设共同因素模型，提出了一种适用于多个响应变量的计算实用形式的概率分析方法。在因素空间上的数值积分提供了概率回归参数以及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的五个变量，其中两个变量先前由阿什福德和索登（1970年，《生物统计学》26卷，535 - 546页）进行了分析。
