UF’s MS in Biostatistics trains students in modern statistical methods used in biomedical, epidemiological, and health research. Courses include survival analysis, longitudinal data modeling, statistical computing, and Bayesian inference. Graduates are well-equipped to analyze complex datasets and contribute to public health, clinical trials, and medical data science.
Survival analysis of cancer patient outcomes based on treatment modality
Design and simulation of adaptive clinical trial protocols
Time-series modeling of COVID-19 transmission and vaccination effects
Multivariate logistic regression model for stroke risk prediction
Missing data imputation strategies for longitudinal cohort studies
Bayesian modeling of treatment response in rare diseases
Meta-analysis of randomized controlled trials in cardiovascular interventions
Development of an R package for generalized estimating equations (GEE)
Study of spatial clustering in vector-borne disease outbreaks
Thesis on hierarchical modeling in multi-center clinical trials
Design of a mobile health app usability study with statistical validation
Classification models using random forests for early cancer detection
Survival modeling for transplant patients using electronic health records
Analysis of behavioral health trends using national BRFSS survey data
Sample size estimation techniques for cluster-randomized trials
Genetic association study using high-dimensional SNP data
Machine learning ensemble techniques for hospital readmission prediction
Evaluation of false discovery control in multiple hypothesis testing
Exploratory factor analysis in mental health scale development
Propensity score matching in observational studies of treatment effects
Build statistical models that reveal patterns in public health and biomedical research.
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