STUDENT HANDBOOK
HOPKINS
PERSPECTIVE ON BIOSTATISTICS: A BRIEF HISTORY AND TODAY
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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