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Research & Practice
Initiatives
Causal Inference in Public Health Research Lab
The Causal Inference in Public Health Research (CIPHR) lab is focused on the development, evaluation, and application of causal inference methods in public health research. Projects range from applications of causal inference methods to answer substantive research questions to the development of new statistical methods. The CIPHR lab provides students an opportunity to get involved in research and learn about causal inference methods.
Study Design & Data Analysis
The Study Design and Data Analysis (SDDA) core enhances research at USF Health by supporting study design, data analysis, and data management. It strengthens grant applications through statistical planning and contributes to funded projects with expert analysis and reporting. The group also ensures independent data management in compliance with NIH guidelines.
Areas of Focus
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Bayesian Statistical Methods
Develops advanced Bayesian methods for analyzing complex data, with a focus on prediction and clinical research design.
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Causal Inference and Mediation Analysis
Applies causal inference techniques to understand the mechanisms through which exposures affect health outcomes.
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Clinical Trials
Designs and analyzes clinical trials to assess the safety and efficacy of new treatments, with a focus on digital and decentralized trials.
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Data Privacy, Synthetic Data, and Data Sharing
Utilizes privacy techniques and machine learning to enable secure data sharing in medical research while protecting patient privacy.
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Longitudinal and Spatial Data Analysis
Analyzes data over time and space to study health trends, disease spread, and resource allocation.
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Biomarker Validation
Develops methods to validate biomarkers for disease detection and treatment response, focusing on optimal study design and bias correction.