A joint marginal-conditional model for multivariate longitudinal data
نویسندگان
چکیده
منابع مشابه
Conditional Dependence in Longitudinal Data Analysis
Mixed models are widely used to analyze longitudinal data. In their conventional formulation as linear mixed models (LMMs) and generalized LMMs (GLMMs), a commonly indispensable assumption in settings involving longitudinal non-Gaussian data is that the longitudinal observations from subjects are conditionally independent, given subject-specific random effects. Although conventional Gaussian...
متن کاملA pairwise interaction model for multivariate functional and longitudinal data.
Functional data vectors consisting of samples of multivariate data where each component is a random function are encountered increasingly often but have not yet been comprehensively investigated. We introduce a simple pairwise interaction model that leads to an interpretable and straightforward decomposition of multivariate functional data and of their variation into component-specific processe...
متن کاملA State Space Model for Multivariate Longitudinal Count Data
A state space model for multivariate longitudinal count data driven by a latent gamma Markov process is proposed, the observed counts being conditionally independent and Poisson distributed given the latent process. We consider regression analysis for this model with time-varying covariates entering either via the Poisson model or via the latent gamma process. We develop the Kalman lter and smo...
متن کاملA mixed-effects regression model for longitudinal multivariate ordinal data.
A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do no...
متن کاملA Transition Model for Multivariate Categorical Longitudinal Data
Riassunto: Per l’analisi di dati categorici longitudinali, viene proposta un’estensione multivariata del modello logistico dinamico. Il modello permette di utilizzare diversi tipi di logit e log-odds ratio per parametrizzare la distribuzione delle variabili risposta (ciascuna delle quali può essere ordinale o non ordinale) in funzione delle covariate, di un vettore di effetti non osservabili e ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistics in Medicine
سال: 2017
ISSN: 0277-6715
DOI: 10.1002/sim.7552