Biostatistics comprises the reasoning and methods for using data as evidence to address public health and biomedical questions. It is an approach and a set of tools for designing studies and for quantifying the resulting evidence, for quantifying what we believe, and for making decisions.

At Johns Hopkins Department of Biostatistics, research is characterized by a commitment to statistical science, its foundations and methods, as well as the application of statistical science to the solution of public health and biomedical problems. As indicated in the two-way arrows in the figure below, research on foundations, methods, and applications is mutually supportive. To be excellent, biostatistical research must be built on a foundation of first-rate public health and biomedical research, like that which occurs at Johns Hopkins.


Foundations            Methodology           Applications


               Public Health and Biomedical Research


Research on foundations has as its goal the development of better strategies, or ways of reasoning, for empirical research.  For example, past chair William Cochran demonstrated how observational studies can be used to draw inferences about the causal effect of a treatment on a health outcome.  Jerry Cornfield showed how case control studies can be used to draw valid inferences about parameters in prospective models.   Richard Royall led a transition in statistical reasoning from decision methods (p-values, tests of hypotheses) toward likelihood methods, which quantify scientific evidence. Charles Rohde, former faculty member Kung-Yee Liang, Tom Louis, Constantine Frangakis, and others continue this tradition.


Research on statistical methodology has as its goal the creation of new tools for drawing inferences from data.  To illustrate, former faculty member Ron Brookmeyer and adjunct faculty member Mitch Gail developed the methodology used to monitor and project the size of the US AIDS epidemic; Kung-Yee Liang, Mei-Cheng Wang, and Scott Zeger developed methods for regression analysis with correlated responses.  Daniel Scharfstein and Constantine Frangakis have developed techniques for assessing the possible impact of missing data in clinical trials and observational studies. Ingo Ruczinski has developed novel regression methods to predict how proteins will fold. 


To accomplish societal goals, biostatistics and biostatisticians must research important substantive questions as well.  For example, former faculty member Francesca Dominici, with Aidan McDermott, and Frank Curriero, and colleagues have used multiple national databases to determine the effects of air pollution on mortality across the 90 largest American cities.  Marie Diener-West, Jim Tonascia, and others have led or collaborated in clinical trials of new therapeutic treatments.  Karen Bandeen-Roche collaborates with gerontologists to determine the causes and course, and ultimately to postpone the onset, of disability in older adults.  The Biostatistics Center faculty, including Richard Thompson, Carol Thompson, and Gayane Yenokyan, serve more than 150 biomedical clients each year.


Throughout its history and today, Hopkins Biostatistics has embraced a broad definition of our discipline, including foundations, methodology, and applications.  The faculty's commitment to this inclusive perspective and the support of the School's administration and faculty are two of the intangible yet critical components of the Department's current and future success.

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