Comput Methods Programs Biomed - Flexible multivariate marginal models for analyzing multivariate longitudinal data, with applications in R.

Tópicos

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{ data(3008) multipl(1320) sourc(1022) }
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{ framework(1458) process(801) describ(734) }
{ imag(2830) propos(1344) filter(1198) }
{ data(1714) softwar(1251) tool(1186) }
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{ group(2977) signific(1463) compar(1072) }
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{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
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Resumo

Most of the available multivariate statistical models dictate on fitting different parameters for the covariate effects on each multiple responses. This might be unnecessary and inefficient for some cases. In this article, we propose a modelling framework for multivariate marginal models to analyze multivariate longitudinal data which provides flexible model building strategies. We show that the model handles several response families such as binomial, count and continuous. We illustrate the model on the Kenya Morbidity data set. A simulation study is conducted to examine the parameter estimates. An R package mmm2 is proposed to fit the model.

Resumo Limpo

avail multivari statist model dictat fit differ paramet covari effect multipl respons might unnecessari ineffici case articl propos model framework multivari margin model analyz multivari longitudin data provid flexibl model build strategi show model handl sever respons famili binomi count continu illustr model kenya morbid data set simul studi conduct examin paramet estim r packag mmm propos fit model

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