The Johns Hopkins University Department of Biostatistics offers the following three graduate programs to those applicants with a bachelor's degree (or higher) interested in professional or academic careers at the interface of the statistical and health sciences:
Hopkins Biostatistics is dedicated to high-quality education. Building on the legacy established by the late Helen Abbey (3 Golden Apples), Marie Diener-West, Jim Tonascia, Scott Zeger, John McGready, and Karen Bandeen-Roche have continued this tradition of educational excellence through their combined total of 20 Golden Apples. As of 2010, faculty members in the department have won a total of 62 Golden Apple Awards for Excellence in Teaching as well as Advising, Mentoring and Teaching Recognition Awards over the years--more than any other department.
Hopkins Perspective on Biostatistics:
comprises the reasoning
and methods for using data as evidence to address public health and
questions. It is an approach
set of tools for designing studies and for quantifying the resulting
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 Figure 1, 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.
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.
Research on statistical methodology has as its goal the creation of new tools for drawing inferences from data. To illustrate, Scott Zeger, together with former faculty member Kung-Yee Liang, and Mei-Cheng Wang developed methods for regression analysis with correlated responses. Dan Scharfstein and colleagues have developed graphical techniques for assessing the possible impact of missing data in clinical trials and observational studies. Constantine Frangakis and colleagues have developed principal stratification, a ground-breaking method to infer causal relationships. Rafael Irizarry has led in the development of statistical methods that have substantially improved the output of gene chip technology. Brian Caffo, Ciprian Crainiceanu and their colleagues are advancing methods to interpet data of massive scope as arise in neurological images, accelerometers, and other advanced research technologies.
also includes research on important substantive questions. For example, faculty
have used multiple national databases to
determine the effects of air pollution on mortality across the 90 largest
and others have
led or collaborated in clinical trials of new therapeutic treatments.
Ingo Ruczinski and his colleagues are identifying genetic determinants of
cancers, autism, cleft lip, and other diseases. Karen
programs, educational initiatives and research to determine the causes and
and ultimately to postpone the onset, of disability and frailty in older
adults. Throughout its history and today, Hopkins Biostatistics has embraced a
broad definition of our discipline, including foundations, methodology, and
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.