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- Causal inference (2)
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Articles 1 - 5 of 5
Full-Text Articles in Biostatistics
Estimating Treatment Effect On Medical Cost And Examining Medical Cost Trajectory Using Splines And Change Point Techniques., Indranil Ghosh
Estimating Treatment Effect On Medical Cost And Examining Medical Cost Trajectory Using Splines And Change Point Techniques., Indranil Ghosh
Electronic Theses and Dissertations
In the world of growing medical needs, other than the clinical outcomes, the cost of healthcare is one of the important aspects to evaluate. The cost of treatment could act as a decisive factor on which one to choose from two equally likely effective treatment options. In literature, the most used quantity for the cost of treatment is cumulative lifetime cost since the diagnosis of a disease. While it provides a bird' eye view of the treatment cost, it fails to capture the underlying pattern of the treatment cost trajectory. We developed a marginal structural functional model (MSFM) using an …
Bayesian Variable Selection Strategies In Longitudinal Mixture Models And Categorical Regression Problems., Md Nazir Uddin
Bayesian Variable Selection Strategies In Longitudinal Mixture Models And Categorical Regression Problems., Md Nazir Uddin
Electronic Theses and Dissertations
In this work, we seek to develop a variable screening and selection method for Bayesian mixture models with longitudinal data. To develop this method, we consider data from the Health and Retirement Survey (HRS) conducted by University of Michigan. Considering yearly out-of-pocket expenditures as the longitudinal response variable, we consider a Bayesian mixture model with $K$ components. The data consist of a large collection of demographic, financial, and health-related baseline characteristics, and we wish to find a subset of these that impact cluster membership. An initial mixture model without any cluster-level predictors is fit to the data through an MCMC …
Predictive Modeling Of Clinical Outcomes For Hospitalized Covid-19 Patients Utilizing Cytof And Clinical Data., Onajia Stubblefield
Predictive Modeling Of Clinical Outcomes For Hospitalized Covid-19 Patients Utilizing Cytof And Clinical Data., Onajia Stubblefield
Electronic Theses and Dissertations
In December 2019, an outbreak of a novel coronavirus initiated a global pandemic. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a virus that causes the disease coronavirus disease 2019 (COVID-19). Symptoms of infection with COVID-19 vary widely between individuals. While some infected individuals are asymptomatic, others need more extensive care and require hospitalization. Indeed, the COVID-19 pandemic was characterized by a shortage of hospital beds which presented additional complications in providing adequate care for patients. In this study, we used a combination of T cell population data collected from mass cytometry analysis and clinical markers to form a predictive …
Estimating Cumulative Incidence Rate On Interval Censored Data In An Illness-Death Model., Chen Qian
Estimating Cumulative Incidence Rate On Interval Censored Data In An Illness-Death Model., Chen Qian
Electronic Theses and Dissertations
Phase IV clinical trials are designed to monitor long-term side effects caused overtime by the medical treatment. For instance, in advanced primary cancer treatment, childhood cancer survivors are often at risk of developing undesired events, such as cardiotoxicity, during their adulthood. Such problems could be due to their cancer or the treatment they received for their cancer such as radiation or intensive chemotherapy. Cardiotoxicity can be diagnosed with electrophysiology with measurements of fraction shortening, afterload, etc. Often the primary focus of a study could be on estimating the cumulative incidence of a particular outcome of interest such as cardiotoxicity. However, …
Observational Studies In Group Testing And Potential Applications., Alexander Christopher Noll
Observational Studies In Group Testing And Potential Applications., Alexander Christopher Noll
Electronic Theses and Dissertations
The use of group testing to identify individuals with targeted outcomes in a population can greatly improve the efficiency, speed, and cost effectiveness of testing a population for an outcome, or at least for identifying the prevalence of an outcome in a population. The implementation of causal inference techniques can provide the basis for an observational study that would allow an investigator to gather estimates for treatment effectiveness if group testing was conducted on the population in a certain way. This thesis examines a simulation of the above outlined principles in order to demonstrate a potential application for determining treatment …