Molenberghs G, Lesaffre E
Biostatistics, Limburgs Universitair Centrum, B3590 Diepenbeek, Belgium.
Stat Med. 1999;18(17-18):2237-55. doi: 10.1002/(sici)1097-0258(19990915/30)18:17/18<2237::aid-sim252>3.0.co;2-r.
This paper describes likelihood methods of analysis for multivariate categorical data. The joint distribution is specified in terms of marginal mean functions, and pairwise and higher order association measures. For the association, the emphasis is on global odds ratios. The method allows flexible formulation of a broad class of designs, such as repeated measurements, longitudinal studies, interrater agreement and cross-over trials. The proposed model can be used for parameter estimation and hypothesis testing. Simple fitting algorithms are proposed. The method is illustrated using a data example.
本文描述了多变量分类数据的似然分析方法。联合分布是根据边际均值函数、成对及高阶关联度量来指定的。对于关联，重点是全局优势比。该方法允许灵活地制定广泛的一类设计，如重复测量、纵向研究、评分者间一致性和交叉试验。所提出的模型可用于参数估计和假设检验。提出了简单的拟合算法。通过一个数据示例对该方法进行了说明。
