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Multilevel Bayesian Models for Survival Times and Longitudinal Patient-Reported Outcomes With Many Zeros

大量零值纵向患者报告结局与生存时间的多层贝叶斯模型

Regulatory approval of new therapies often depends on demonstrating prolonged survival. Particularly when these survival benefits are modest, consideration of therapeutic benefits to patient-reported outcomes (PROs) may add value to the traditional biomedical clinical trial endpoints. We extend a popular class of joint models for longitudinal and survival data to accommodate the excessive zeros common in PROs, building hierarchical Bayesian models that combine information…

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Bayesian Tobit Modeling of Longitudinal Ordinal Clinical Trial Compliance Data with Nonignorable Missingness

存在不可忽略缺失的纵向有序临床试验依从性数据:贝叶斯 Tobit 建模

In the Lung Health Study (LHS), compliance with the use of inhaled medication was assessed at each follow-up visit both by self-report and by weighing the used medication canisters. One or both of these assessments were missing if the participant failed to attend the visit or to return all canisters. Approximately 30% of canister-weight data and 5% to 15% of self-report data were missing at different visits. We use Gibbs sampling with data augmentation and a multivariate…

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Bayesian Tobit Modeling of Longitudinal Ordinal Clinical Trial Compliance Data With Nonignorable Missingness

存在不可忽略缺失的纵向有序临床试验依从性数据:贝叶斯 Tobit 建模

In the Lung Health Study (LHS), compliance with the use of inhaled medication was assessed at each follow-up visit both by self-report and by weighing the used medication canisters. One or both of these assessments were missing if the participant failed to attend the visit or to return all canisters. Approximately 30% of canister-weight data and 5% to 15% of self-report data were missing at different visits. We use Gibbs sampling with data augmentation and a multivariate…

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Hierarchical Bayes Models for the Progression of HIV Infection Using Longitudinal CD4 T-Cell Numbers

利用纵向CD4 T细胞数量研究HIV感染进展的层级贝叶斯模型

Taking the absolute number of CD4 T-cells as a marker of disease progression for persons infected with the human immunodeficiency virus (HIV), we model longitudinal series of such counts for a sample of 327 subjects in the San Francisco Men's Health Study (Waves 1–8, excluding zidovudine cases). We conduct a fully Bayesian analysis of these data. We employ individual level nonlinear models incorporating such critical features as incomplete and unbalanced data, population…

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