Random coefficient repeated measures models
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چکیده
منابع مشابه
On the Performance of Random-coefficient Pattern-mixture Models for Nonignorable Attrition
Missing observations are common in longitudinal studies. In this article, we focus on attrition or dropout, where responses are available for a subject until a certain occasion and missing for all subsequent occasions. We also limit our discussion to the analysis of a single continuous response variable over time; applications to discrete and multivariate repeated measures are computationally m...
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Analysis of repeated measures data for the purpose of prediction is not an easy task particularly when the problem under consideration is highly nonlinear, number of subjects is large and the sample available to learn the model is small. The efficacy of the ANN for subject level treatment has been studied here empirically. Data were generated through a random coefficient model and a few nonline...
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The analysis of longitudinal repeated measures data is frequently complicated by missing data due to informative dropout. We describe a mixture model for joint distribution for longitudinal repeated measures, where the dropout distribution may be continuous and the dependence between response and dropout is semiparametric. Specifically, we assume that responses follow a varying coefficient rand...
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Background and purpose: To analyze the data in which the correlation between observations are to be considered, a general method is using marginal model with repeated measures, yet there is another method called conditional model with random clusters. Âccording to the binary responses, the aim of the present study is to compare the efficiency of these two models in studying the risk factors a...
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A version of the nonlinear mixed-effects model is presented that allows random effects only on the linear coefficients. Nonlinear parameters are not stochastic. In nonlinear regression, this kind of model has been called conditionally linear. As a mixed-effects model, this structure is more flexible than the popular linear mixed-effects model, while being nearly as straightforward to estimate. ...
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