Clustering for multivariate continuous and discrete longitudinal data
نویسندگان
چکیده
منابع مشابه
Clustering for Multivariate Continuous and Discrete Longitudinal Data
Multiple outcomes, both continuous and discrete, are routinely gathered on subjects in longitudinal studies and during routine clinical follow-up in general. To motivate our work, we consider a longitudinal study on patients with primary biliary cirrhosis (PBC) with a continuous bilirubin level, a discrete platelet count and a dichotomous indication of blood vessel malformations as examples of ...
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R package mixAK originally implemented routines primarily for Bayesian estimation of finite normal mixture models for possibly interval-censored data. The functionality of the package was considerably enhanced by implementing methods for Bayesian estimation of mixtures of multivariate generalized linear mixed models proposed in Komárek and Komárková (2013). Among other things, this allows for a...
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Since different distributions and link functions have to be used for the different outcomes, we use a special device available in the SAS procedure PROC GLIMMIX, i.e., the ‘byobs=(.)’ specification that can be used to specify both the distribution in the ‘dist=’ option and the link function in the ‘link=’ option. Thus, before we start with the main analysis, two variables need to be created to ...
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Longitudinal data sets are comprised of repeated observations of an outcome and a set of covariates for each of many subjects. One objective of statistical analysis is to describe the marginal expectation of the outcome variable as a function of the covariates while accounting for the correlation among the repeated observations for a given subject. This paper proposes a unifying approach to suc...
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Model-based clustering is considered for Gaussian multivariate functional data as an extension of the univariate functional setting. Principal components analysis is introduced and used to define an approximation of the notion of density for multivariate functional data. An EM like algorithm is proposed to estimate the parameters of the reduced model. Application on climatology data illustrates...
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ژورنال
عنوان ژورنال: The Annals of Applied Statistics
سال: 2013
ISSN: 1932-6157
DOI: 10.1214/12-aoas580