Biostatistics: The near future

Scott Zeger, Peter Diggle, Kung Yee Liang

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.

Original languageEnglish (US)
Title of host publicationCelebrating Statistics
Subtitle of host publicationPapers in Honour of Sir David Cox on his 80th Birthday
PublisherOxford University Press
Volume9780198566540
ISBN (Electronic)9780191718038
ISBN (Print)9780198566540
DOIs
StatePublished - Sep 1 2007

Keywords

  • Bioinformatics
  • Causal inference
  • Conditional inference
  • Genomic data
  • Model complexity
  • Multi-level models
  • Nuisance parameters
  • Statistical computing
  • Statistical efficiency

ASJC Scopus subject areas

  • Mathematics(all)

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