BRP staff conduct independent and collaborative biostatistical research. This includes developing new biostatistical methodology as well as evaluating currently used methods. The methods investigated by BRP staff include methods useful for the design, monitoring and analysis of clinical trials; the design and analysis of biomarker studies; sampling methods and methods for the analysis of observational data; design and analysis of imaging studies; analysis of laboratory assay data; and analysis of genomic data. Current major research interests of the staff include:

• Clinical trials methodology including design, monitoring and analysis issues
• Bayesian methods in clinical trial design and analysis
• Multiple comparisons, including application to high-dimensional genomic data
• Clustering and prediction methods appropriate for high-dimensional genomic data
• Survival analysis, with special emphasis on randomized clinical trials
• Analysis of genetic data including familial association analysis
• Longitudinal data analysis
• Diagnostic and measurement error
• Design and analysis of biomarker assay evaluation studies
• Laboratory quality control
• Missing data
• Smoothing methods
• Nonparametric statistical methods
• Analysis methods of complex health surveys
• Spatial statistics
• ROC analysis and regression