Our researchers are nationally recognized experts in biostatistics. Their work affects medical research, health care, genetic research, cancer research, and biometrics.
Here’s a look at our faculty’s expertise
Scott Bruce is developing novel statistical methods for the analysis of time series and longitudinal data generated from modern experimental and observational studies in areas such as sleep research, neuroscience, and psychiatry. Many applications in these fields are not served holistically by existing theory and methods. Bruce is passionate about developing practical, computationally efficient analytical tools that address and utilize the full nature of the complexity underlying the data-generating process. In one of his recent works, he explores frequency-domain approaches for assessing associations between temporally evolving data and outcomes of interest, which can be applied to analyze the relationship between sleep quality and heart rate variability during sleep.
Guoqing Diao’s research focuses on developing novel statistical methods for the designs and analyses of biomedical and public health studies. His current research areas include precision medicine, survival analysis, semiparametric models, longitudinal data analysis, high-dimensional data analysis, statistical genetics, policing and crime prevention, and rare event simulation problems. He has published extensively in statistical journals including Biometrics, Biometrika, and the Annals of Applied Probability, and medical journals such as American Journal of Human Genetics and PM&R. The National Science Foundation, the National Institutes of Health, and industry partners support his research.
Niloofar Ramezani has developed two new power estimation techniques for longitudinal data using generalized method of moments. These methods are capable of handling both time-dependent and time-independent covariates. She also works on developing and applying advanced novel statistical models with high efficiency, within the framework of longitudinal and joint models, including joint modeling of mean and dispersion. She is passionate and involved in handling missing data, semiparametric modeling of survival data, efficiently modeling correlated and multilevel data, and extending generalized estimating equations to capture a higher response variation. Such methods are used frequently in the biomedical, public health, engineering, business, and econometric fields.
William Rosenberger develops methodology for the design and analysis of randomized clinical trials to help scientists determine which new experimental treatments are effective. He is particularly interested in designing clinical trials for rare diseases, which led him to serve as a member of an international advisory board for a European Union consortium on small population clinical trials. Changing the way the studies are conducted could make it easier for people to get new therapies earlier and potentially save lives. He has written two books on the subject, Randomization in Clinical Trials: Theory and Practice and The Theory of Response-Adaptive Randomization in Clinical Trials.
Anand Vidyashankar's primary research interests involve biostatistics, statistics, and biotechnology, statistical models for the internet, statistics in finance, data confidentiality, probability, and stochastic processes. The National Science Foundation and industry partners support his research.