mmm: An R package for analyzing multivariate longitudinal data with multivariate marginal models

被引:17
作者
Asar, Oezguer [1 ]
Ilk, Ozlem [2 ]
机构
[1] Fac Hlth & Med, Lancaster Med Sch, CHICAS, Lancaster LA1 4YG, England
[2] Middle E Tech Univ, Fac Arts & Sci, Dept Stat, TR-06800 Ankara, Turkey
关键词
Correlated data; Multiple outcomes; Medical studies; Package presentation; Population-averaged inference; Statistical software; REGRESSION; RESPONSES; DISCRETE; DECLINE;
D O I
10.1016/j.cmpb.2013.07.022
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Modeling multivariate longitudinal data has many challenges in terms of both statistical and computational aspects. Statistical challenges occur due to complex dependence structures. Computational challenges are due to the complex algorithms, the use of numerical methods, and potential convergence problems. Therefore, there is a lack of software for such data. This paper introduces an R package mmm prepared for marginal modeling of multivariate longitudinal data. Parameter estimations are achieved by generalized estimating equations approach. A real life data set is applied to illustrate the core features of the package, and sample R code snippets are provided. It is shown that the multivariate marginal models considered in this paper and mmm are valid for binary, continuous and count multivariate longitudinal responses. (c) 2013 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:649 / 654
页数:6
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