Modelling measurement errors and category misclassifications in multilevel models
Modelling measurement errors and category misclassifications in multilevel models
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DOI：
10.1177/1471082x0800800302
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发表时间：
2008-10-01
影响因子：
1
通讯作者：
Robinson, Anthony
中科院分区：
文献类型：
--
作者：
Goldstein, Harvey;Kounali, Daphne;Robinson, Anthony
开发模型是为了调整正态分布的预测变量和响应变量以及具有错误分类错误的分类预测变量中的测量误差。该模型允许分层数据结构以及错误和错误分类之间的相关性。马尔可夫链蒙特卡罗 (MCMC) 估计在一组 MATLAB 宏中使用和实现。
Models are developed to adjust for measurement errors in normally distributed predictor and response variables and categorical predictors with misclassification errors. The models allow for a hierarchical data structure and for correlations among the errors and misclassifications. Markov Chain Monte Carlo (MCMC) estimation is used and implemented in a set of MATLAB macros.