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Celebrating StatisticsPapers in honour of Sir David Cox on his 80th birthday$
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A. C. Davison, Yadolah Dodge, and N. Wermuth

Print publication date: 2005

Print ISBN-13: 9780198566540

Published to Oxford Scholarship Online: September 2007

DOI: 10.1093/acprof:oso/9780198566540.001.0001

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Biostatistics: the near future

Biostatistics: the near future

Chapter:
(p.167) 8 Biostatistics: the near future
Source:
Celebrating Statistics
Author(s):

Scott Zeger

Peter Diggle

Kung-Yee Liang

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198566540.003.0009

This chapter reviews the biomedical and public health developments that will influence biostatistical research and practice in the near future, such as advances in molecular biology, and measuring DNA sequences and gene and protein expression levels. It is argued that the success of biostatistics will derive largely from a model-based approach, which uses and applies the principle of conditioning. Statistical models and inferences that are central to this model-based approach are described and contrasted with computationally-intensive strategies and a design-based approach. Increasingly complex models, different sources of uncertainty, and clustered observational units are viewed as future challenges for the model-based approach. Causal inference and statistical computing are discussed as topics believed to be central to biostatistics in the near future.

Keywords:   bioinformatics, causal inference, conditional inference, genomic data, model complexity, multi-level models, nuisance parameters, statistical efficiency, statistical computing

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