Ekholm Anders, Jokinen Jukka, McDonald John W, Smith Peter W F
Rolf Nevanlinna Institute, P.O. Box 4, FIN-00014 University of Helsinki, Finland.
Biometrics. 2003 Dec;59(4):795-803. doi: 10.1111/j.0006-341x.2003.00093.x.
We propose models for longitudinal, or otherwise clustered, ordinal data. The association between subunit responses is characterized by dependence ratios (Ekholm, Smith, and McDonald, 1995, Biometrika 82, 847-854), which are extended from the binary to the multicategory case. The joint probabilities of the subunit responses are expressed as explicit functions of the marginal means and the dependence ratios of all orders, obtaining a computational advantage for likelihood-based inference. Equal emphasis is put on finding regression models for the univariate cumulative probabilities, and on deriving the dependence ratios from meaningful association-generating mechanisms. A data set on the effects of treatment with Fluvoxamine, which has been analyzed in parts before (Molenberghs, Kenward, and Lesaffre, 1997, Biometrika 84, 33-44), is analyzed in its entirety. Selection models are used for studying the sensitivity of the results to drop-out.
我们提出了适用于纵向或其他聚类有序数据的模型。亚单位反应之间的关联由依存比来表征（埃克霍尔姆、史密斯和麦克唐纳，1995年，《生物统计学》82卷，第847 - 854页），该依存比从二元情况扩展到了多类别情况。亚单位反应的联合概率被表示为边际均值和所有阶次依存比的显式函数，从而在基于似然的推断中获得计算优势。我们同样重视寻找单变量累积概率的回归模型，以及从有意义的关联生成机制中推导依存比。对一个关于氟伏沙明治疗效果的数据集进行了完整分析，该数据集之前已有部分分析（莫伦伯格斯、肯沃德和莱斯弗雷，1997年，《生物统计学》84卷，第33 - 44页）。选择模型用于研究结果对失访的敏感性。
