Reporting on statistical methods to adjust for confounding: a cross-sectional survey

Ann Intern Med. 2002 Jan 15;136(2):122-6. doi: 10.7326/0003-4819-136-2-200201150-00009.


Background: The use of complex statistical models to adjust for confounding is common in medical research.

Objective: To determine the frequency and adequacy of adjustment for confounding in medical articles.

Design: Cross-sectional survey.

Setting: 34 scientific medical journals with a high impact factor.

Measurements: Frequency of reporting on methods used to adjust for confounding in 537 original research articles published in January 1998.

Results: Of the 537 articles, 169 specified that adjustment for confounding was used. In 1 paper in 10, it was unclear which statistical method was used or for which variables adjustment was made. In 45% of papers, it was not clear how multicategory or continuous variables were treated in the analysis. Inadequate reporting was less frequent if an author was affiliated with a department of statistics, epidemiology, or public health and if articles were published in journals with a high impact factor.

Conclusions: Details of methods used to adjust for confounding are frequently not reported in original research articles.

MeSH terms

  • Confounding Factors, Epidemiologic*
  • Cross-Sectional Studies
  • Humans
  • Periodicals as Topic / standards
  • Randomized Controlled Trials as Topic / standards
  • Research Design / standards*
  • Statistics as Topic / standards*