Biostatistics in Australia: Directions in the new millennium

The Biostatistics Collaboration of Australia (BCA) was formed in response to a shortage of statisticians seeking careers in the medical and health professions. The Collaboration has been successful in developing postgraduate courses (Graduate Certificate, Graduate Diploma and Masters) offered by a consortium of seven Australian Universities. These courses are available through a distance learning medium. The BCA was successful in securing funding from the Federal government to launch these courses, which commenced in March 2001. Two traineeships by the NSW Department of Health have also been awarded and a third is currently advertised. There has been close collaboration with governments, the pharmaceutical industry and research organisations to ensure that course content reflects practical problems and addresses industry needs. A second objective of the BCA is to provide ongoing workshops for practising biostatisticians to enhance professional development. These workshops serve to ring together biostatisticians from both within Australia and the Asia-Pacific region, providing a forum for discussion of current statistical thinking. (author abstract)

A Cox Model for Biostatistics of the Future

Professor Sir David R. Cox (DRC) is widely acknowledged as among the most important scientists of the second half of the twentieth century. He inherited the mantle of statistical science from Pearson and Fisher, advanced their ideas, and translated statistical theory into practice so as to forever change the application of statistics in many fields, but especially biology and medicine. The logistic and proportional hazards models he substantially developed, are arguably among the most influential biostatistical methods in current practice. This paper looks forward over the period from DRC's 80th to 90th birthdays, to speculate about the future of biostatistics, drawing lessons from DRC's contributions along the way. We consider "Cox's model" of biostatistics, an approach to statistical science that: formulates scientific questions or quantities in terms of parameters gamma in probability models f(y; gamma) that represent in a parsimonious fashion, the underlying scientific mechanisms (Cox, 1997); partition the parameters gamma = theta, eta into a subset of interest theta and other "nuisance parameters" eta necessary to complete the probability distribution (Cox and Hinkley, 1974); develops methods of inference about the scientific quantities that depend as little as possible upon the nuisance parameters (Barndorff-Nielsen and Cox, 1989); and thinks critically about the appropriate conditional distribution on which to base infrences. We briefly review exciting biomedical and public health challenges that are capable of driving statistical developments in the next decade. We discuss the statistical models and model-based inferences central to the CM approach, contrasting them with computationally-intensive strategies for prediction and inference advocated by Breiman and others (e.g. Breiman, 2001) and to more traditional design-based methods of inference (Fisher, 1935). We discuss the hierarchical (multi-level) model as an example of the future challanges and opportunities for model-based inference. We then consider the role of conditional inference, a second key element of the CM. Recent examples from genetics are used to illustrate these ideas. Finally, the paper examines causal inference and statistical computing, two other topics we believe will be central to biostatistics research and practice in the coming decade. Throughout the paper, we attempt to indicate how DRC's work and the "Cox Model" have set a standard of excellence to which all can aspire in the future.

Shaping the Future of Public Health: The Role of Biostatistics

Comments about the current place for the discipline of Biostatistics within Public Health (1993).

Venezuela, summary of biostatistics. Maps and charts, population, natality and morality statistics.

Loose-leaf; reproduced from type-written copy.

Nicaragua, summary of biostatistics. Maps and charts, population, natality and mortality statistics.

Reproduced from type-written copy.

Peru, summary of biostatistics. Maps and charts, population, natality and mortality statistics.

Reproduced from type-written copy.

Uruguay, summary of biostatistics. Maps and charts, population, natality and mortality statistics.

Reproduced from type-written copy.

Cuba, summary of biostatistics : maps and charts, population, natality, and mortality, statistics /

Limited cataloging.

Argentina, summary of biostatistics. Maps and charts, population, natality and mortality statistics.

Reproduced from type-written copy.

Bolivia, summary of biostatistics; Maps and charts, population, natality and mortality statistics,

Mode of access: Internet.

Colombia, summary of biostatistics. Maps and charts, population, natality and mortality statistics.

Reproduced from typewritten copy.

Report on the Inter-American Seminar for Biostatistics, held at Santiago, Chile, from 25 September to 15 December 1950 /

Mode of access: Internet.

Biostatistics of the USAF Medical Service: annual report.

Mode of access: Internet.