Statistics in medical research

Swiss Med Wkly. 2003 Oct 11;133(39-40):522-9.

Abstract

The role of statistics in medical research starts at the planning stage of a clinical trial or laboratory experiment to establish the design and size of an experiment that will ensure a good prospect of detecting effects of clinical or scientific interest. Statistics is again used during the analysis of data (sample data) to make inferences valid in a wider population. In simple situations computation of simple quantities such as P-values, confidence intervals, standard deviations, standard errors or application of some standard parametric or nonparametric tests may suffice. Despite their wide use even these simple notions are sometimes misunderstood or misinterpreted by research workers in other disciplines who have only a limited knowledge of statistics. More sophisticated research projects often need advanced statistical methods including the formulation and testing of mathematical models to make relevant inferences from observed data. Such advanced methods should only be applied with a clear understanding both of their purposes and the implication of any conclusions based upon their use. Close collaboration between statisticians, whether professionals in that field or medical research workers with a sound statistical background, and other members of a research team is needed to ensure a seamless integration of the statistical elements into the reporting and discussion of research outcomes. Some suggestions are made as to how that collaboration is best achieved.

Publication types

  • Review

MeSH terms

  • Biomedical Research / statistics & numerical data*
  • Clinical Trials as Topic / statistics & numerical data
  • Cooperative Behavior
  • Data Interpretation, Statistical
  • Humans
  • Reproducibility of Results
  • Research Design / statistics & numerical data
  • Statistics as Topic* / education
  • Workforce