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Competing regression models for longitudinal data
(WILEY-BLACKWELLMALDEN, 2012)
The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing ...
Competing regression models for longitudinal data
(Wiley-Blackwell, 2012-03-01)
The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing ...
A model-based approach to Bayesian classification with applications to predicting pregnancy outcomes from longitudinal beta-hCG profiles
(OXFORD UNIV PRESS, 2007)
This paper discusses Bayesian statistical methods for the classification of observations into two or more groups based on hierarchical models for nonlinear longitudinal profiles. Parameter estimation for a discriminant ...
Formulating Mixed Models for Experiments, Including Longitudinal Experiments
(AMER STATISTICAL ASSOC & INT BIOMETRIC SOC, 2009)
Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving ...
Bayesian longitudinal data analysis with mixed models and thick-tailed distributions using MCMC
(Carfax Publishing, 2004-08-01)
Linear mixed effects models are frequently used to analyse longitudinal data, due to their flexibility in modelling the covariance structure between and within observations. Further, it is easy to deal with unbalanced data, ...
Semiparametric Bayesian classification with longitudinal markers
(BLACKWELL PUBLISHING, 2007)
We analyse data from a study involving 173 pregnant women. The data are observed values of the beta human chorionic gonadotropin hormone measured during the first 80 days of gestational age, including from one up to six ...
Bayesian longitudinal data analysis with mixed models and thick-tailed distributions using MCMC
(Carfax Publishing, 2014)
Longitudinal Poisson modeling: an application for CD4 counting in HIV-infected patients
(ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTDLONDON, 2010)
In this paper, we present different ofrailtyo models to analyze longitudinal data in the presence of covariates. These models incorporate the extra-Poisson variability and the possible correlation among the repeated counting ...
Bayesian first order auto-regressive latent variable models for multiple binary sequences
(SAGE PUBLICATIONS LTD, 2011)
Longitudinal clinical trials often collect long sequences of binary data monitoring a disease process over time. Our application is a medical study conducted in the US by the Veterans Administration Cooperative Urological ...
New contributions to joint models of longitudinal and survival outcomes : two-stage approaches
(2021)
Joint models of longitudinal and survival outcomes have gained much popularity over the last three decades. This type of modeling consists of two submodels, one longitudinal and one survival, which are connected by some ...