PubMed · 11790063
Reporting on statistical methods to adjust for confounding: a cross-sectional survey.
Abstract
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.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Marcus Müllner, Hugh Matthews, Douglas G Altman. 2002-01-15. Reporting on statistical methods to adjust for confounding: a cross-sectional survey.. https://doi.org/10.7326/0003-4819-136-2-200201150-00009
Cite the original work for its findings. Save a collection to share your selection of sources.