%0 Journal Article %J Annals of Applied Statistics %D 2015 %T Covariance pattern mixture models for the analysis of multivariate heterogeneous longitudinal data %A Anderlucci, Laura %A Cinzia Viroli %K Demographics %K Health Conditions and Status %K Methodology %X We propose a novel approach for modeling multivariate longitudinal data in the presence of unobserved heterogeneity for the analysis of the Health and Retirement Study (HRS) data. Our proposal can be cast within the framework of linear mixed models with discrete individual random intercepts; however, differently from the standard formulation, the proposed Covariance Pattern Mixture Model (CPMM) does not require the usual local independence assumption. The model is thus able to simultaneously model the heterogeneity, the association among the responses and the temporal dependence structure. We focus on the investigation of temporal patterns related to the cognitive functioning in retired American respondents. In particular, we aim to understand whether it can be affected by some individual socio-economical characteristics and whether it is possible to identify some homogenous groups of respondents that share a similar cognitive profile. An accurate description of the detected groups allows government policy interventions to be opportunely addressed. Results identify three homogenous clusters of individuals with specific cognitive functioning, consistent with the class conditional distribution of the covariates. The flexibility of CPMM allows for a different contribution of each regressor on the responses according to group membership. In so doing, the identified groups receive a global and accurate phenomenological characterization. %B Annals of Applied Statistics %I 9 %V 9 %P 777-800 %G eng %N 2 %4 methodology/temporal patterns/cognitive functioning/socioeconomic Differences %$ 999999 %R 10.1214/15-aoas816 %0 Journal Article %J AStA Advances in Statistical Analysis %D 2014 %T A factor mixture model for analyzing heterogeneity and cognitive structure of dementia %A Cagnone, Silvia %A Cinzia Viroli %K Health Conditions and Status %K Methodology %K Other %X The Health and Retirement Study (HRS) is funded by the National Institute on Aging of US with the aim of investigating the health, social and economic implications of the aging of the American population. The participants of the study receive a thorough in-home clinical and neuropsychological assessment leading to a diagnosis of normal, cognitive impairment but not demented, or dementia. Due to the heterogeneity of the participants into three classes, we analyze some overall cognitive functioning responses through a factor mixture analysis model. The model extends recent proposals developed for binary and continuous data to general mixed data and to the situation of observed heterogeneity, typical of the HRS study. %B AStA Advances in Statistical Analysis %I 98 %V 98 %P 1 %G eng %N 1 %4 Latent variables/Categorical and ordinal data/Mixture models/Cognitive functioning/Statistics/Statistics/Statistics, general/Analysis/Econometrics/Dementia/Statistics for Business/Economics/Mathematical Finance/Insurance/Probability Theory and Stochastic Processes %$ 999999 %0 Journal Article %J Statistics in Medicine %D 2012 %T Using factor mixture analysis to model heterogeneity, cognitive structure, and determinants of dementia: an application to the Aging, Demographics, and Memory Study %A Cinzia Viroli %K Health Conditions and Status %X The Aging, Demographics, and Memory Study is the first extensive study of cognitive impairment and dementia of population in the USA. A large sample of participants with ages 71?years or older has answered an in-depth questionnaire which included an extensive cognitive assessment. One of the principal aims of the study was to assign a diagnosis of dementia, cognitive impairment but not demented, or normal to the respondents. Because of this heterogeneity, we apply factor mixture model to the set of neuropsychological measures of the study in order to perform clustering of subjects and dimension reduction simultaneously. Moreover, we consider an extended variant of the model by incorporating a set of demographics and clinical covariates which directly affect the latent variables of the factor mixture model. The interest of the analysis is to investigate whether respondents exhibit the same association of overall cognitive functioning with the covariates or whether groups of respondents exist that exhibit different association with the covariates, indicating different determinants of overall cognitive functioning. Copyright (C) 2012 John Wiley and Sons, Ltd. %B Statistics in Medicine %I 31 %V 31 %P 2110-2122 %G eng %N 19 %4 dementia/Cognitive Impairment/cognitive ability/neuropsychological Tests/cognitive Functioning/ADAMS %$ 69702 %R 10.1002/sim.5320