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Showing 1 to 4 of 4 for “"error-in-covariates"”.
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Dealing with measurement error in covariates with special reference to logistic regression model: a flexible parametric approach
In many fields of statistical application the fundamental task is to quantify the association between some explanatory variables or covariates and a response or outcome variable through a suitable regression model. The accuracy of such quantification depends on how precisely we measure the relevant …
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Dynamic models for time-varying outcomes: An application to the 2015-2017 patient cohort on antiretroviral therapy at Luderitz hospital, Namibia
… to successful antiretroviral therapy (ART). In addition, adherence to ART is one of the key determinants of Human Immunodeficiency Virus (HIV) disease progression, while non-adherence severely compromises treatment effectiveness and leads to unsuppressed virus. The extent of the impact of …
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Semiparametric Regression Methods with Covariate Measurement Error
In public health, biomedical, epidemiological, and other applications, data collected are often measured with error. When mismeasured data is used in a regression analysis, not accounting for the measurement error can lead to incorrect inference about the relationships between the covariates and …
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Semiparametric and Nonparametric Methods for Complex Data
A variety of complex data has broadened in many research fields such as epidemiology, genomics, and analytical chemistry with the development of science, technologies, and design scheme over the past few decades. For example, in epidemiology, the matched case-crossover study design is used to …