John McGready, MS, PhD

John McGready has a MS in Biostatistics from Harvard (1996) and a PhD in Biostatistics from the Johns Hopkins Bloomberg School (2007).

While at Harvard, John was involved in both research and teaching activities. He worked as a research assistant on the Woman Infant Transmission Study (WITS), a multi-center longitudinal study investigating factors related to HIV transmission from mother to infant, and as a researcher. John served as a teaching assistant for several introductory biostatistics courses, for which he received the school wide TA recognition award in 1996.

After his graduate studies, John worked as a research associate at the Urban Institute, an independent policy research center in Washington, DC. His area of work involved research and evaluation of criminal justice policies and programs. This experience allowed John to be involved in all facets of the social science research process: data management and maintenance, study and survey design, interviewing, and analysis. John also applied traditional statistical methods to new uses, such as borrowing techniques from survival analysis to estimate changes in the Federal prison population under sentencing reforms.

Prior to coming to Hopkins, John also spent one year teaching high school mathematics in Washington, DC. Since joining the faculty at Hopkins, John has split his time between statistical consulting and statistical education. In the 2004 academic year, he served as the instructor for both the online and on-site offerings of "Statistical Reasoning in Public Health." In 2001 ,2004, and 2008 John was awarded a "Golden Apple" award for excellence in in-campus teaching by the student body at the Johns Hopkins Bloomberg School of Public Health. In 2001 and 2005 he received the "Golden Apple" award for excellence in online education, as voted by students enrolled in internet-based courses (the award has since been merged with the Golden Apple given for on-campus teaching).

John’s  research interests include comparing classical and less "traditional" approaches to statistical estimation and inference in small sample scenarios and developing a framework to incorporate these alternative approaches (resampling, Bayesian, and Likelihood methods) into an introductory biostatistical curriculum.  He is also actively involved in projects related to genetic medicine and mental health of HIV patients.