A5049086195- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Genetic Neurodegenerative Diseases
- Statistics Education and Methodologies
- Advanced Causal Inference Techniques
- Health and Medical Research Impacts
- Data-Driven Disease Surveillance
- Electoral Systems and Political Participation
- Neurological Disease Mechanisms and Treatments
- Fibromyalgia and Chronic Fatigue Syndrome Research
- Retinal Imaging and Analysis
- Statistical Methods in Clinical Trials
- Bone health and osteoporosis research
- Pharmacological Effects and Toxicity Studies
- Dementia and Cognitive Impairment Research
- Therapeutic Uses of Natural Elements
- Genetic and phenotypic traits in livestock
University of North Carolina at Chapel Hill
2023-2025
Duke University
2023-2024
Objective: Spiritual well-being (SWB) has been shown to delay the onset of cognitive decline among older adults predisposed Alzheimer's disease and related neurodegenerative dementias. It was, however, unknown if SWB is also associated with in manifestation ("phenoconversion") rare, genetic dementias, such as Huntington's (HD). Thus, we sought evaluate association between phenocovnersion people at-risk for HD. Methods: The "Prospective Huntington At Risk Observation Study" (PHAROS), a...
The landscape of survival analysis is constantly being revolutionized to answer biomedical challenges, most recently the statistical challenge censored covariates rather than outcomes. There are many promising strategies tackle covariates, including weighting, imputation, maximum likelihood, and Bayesian methods. Still, this a relatively fresh area research, different from areas outcomes (i.e., analysis) or missing covariates. In review, we discuss unique challenges encountered when handling...
The predominant model for biomedical research is team science. Two critical members of the are clinical investigator and biostatistician. Typically, biostatistician performs statistical analyses interprets results. Clinical investigators have different background interests than biostatisticians, should be taught statistics differently. Concepts phrased in plain language, illustrations replace mathematical derivations, underlying concepts explicitly named. Consistent with basic principles...
Abstract Background Vision impairment is a common complication of stroke, which has been linked to cognitive decline in stroke survivors. Little known about how specific types vision influence the relationship between and dementia. The aims this project were: (1) characterize prevalence both pre‐stroke stroke‐related impairment(s) among survivors with without mild (MCI) or dementia, (2) determine associations impairment, depression, physical performance. Methods Data from Atherosclerosis...
Within a 2-year Master of Biostatistics program, we reconsidered the mathematics requirements for admission, and also premise that most distinguishing feature top candidate is deep exposure to mathematics. Our assessment took place within broad curriculum review intended enhance alignment: aligning programmatic goals with job skills, use our goals, admission criteria curriculum, application materials these criteria. We developed specific list mathematical skills required by are revising...
While right-censored time-to-event outcomes have been studied for decades, handling covariates, also known as is now of growing interest. So far, the literature has treated covariates distinct from missing overlooking potential applicability estimators to both scenarios. We bridge this gap by establishing connections between and under various assumptions about censoring missingness, allowing us identify parallels differences determine when can be used in contexts. These reveal adaptations...
Despite its drawbacks, the complete case analysis is commonly used in regression models with incomplete covariates. Understanding when will lead to consistent parameter estimation vital before use. Our aim here demonstrate a for randomly right-censored covariates and discuss implications of use even consistent. Across censored covariate literature, different assumptions are made ensure produces estimator, which leads confusion practice. We make several contributions dispel this confusion....
Despite its drawbacks, the complete case analysis is commonly used in regression models with missing covariates. Understanding when implementing cases will lead to consistent parameter estimation vital before use. Here, our aim demonstrate a appropriate for nuanced type of covariate, randomly right-censored covariate. Across censored covariate literature, different assumptions are made ensure produces estimator, which leads confusion practice. We make several contributions dispel this...