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- Title
Bayesian semiparametric growth models for measurement error and missing data in CD4/CD8 ratio: Application to AIDS Study.
- Authors
Dagne, Getachew A
- Abstract
In clinical research and practice, there is often an interest in assessing the effect of time varying predictors, such as CD4/CD8 ratio, on immune recovery following antiretroviral therapy. Such predictors are measured with errors, and ignoring those measurement errors during data analysis may lead to biased results. Though parametric methods have been used for reducing biases, they usually depend on untestable assumptions. To relax those assumptions, this paper presents semiparametric mixed-effect models which deal with predictors having measurement errors and missing values. We develop a fully Bayesian approach for fitting these models and discriminating between patients who are potentially progressors or nonprogressors to severe disease condition (AIDS). The proposed methods are demonstrated using real data from an AIDS clinical study.
- Subjects
ERRORS-in-variables models; MEASUREMENT errors; AIDS; MISSING data (Statistics); GROWTH curves (Statistics); ANTIRETROVIRAL agents; ANTI-HIV agents; DISEASE progression; VIRAL load; STATISTICAL models; PROBABILITY theory
- Publication
Statistical Methods in Medical Research, 2020, Vol 29, Issue 1, p178
- ISSN
0962-2802
- Publication type
journal article
- DOI
10.1177/0962280219826403