The current use of statistics in biomedical investigation: A comparison of general medicine journals

Author(s): Terren, C. A., Vilalta, J. S.

Journal/Book: Med Clin. 1996; 106: Trav de Gracia 17-21, 08021 Barcelona, Spain. Ediciones Doyma S/A. 451-456.

Abstract: BACKGROUND: The use of statistical techniques has become strongly consolidated in biomedical investigation. The present study analyzes the statistical repertoire of the original articles published in 1993 in four general medicine journals: Med Clin (Rare), Rev Clin Esp, Lancet and N Engl J Med. METHODS: A single reviewer examined 100 original articles from Med Clin (Bare), 42 from Rev Clin Esp, 105 from Lancet and 116 from N Engl J Med, studying the use of 18 categories of statistical analysis and the statistical accessibility of the reader. The criteria for assigning techniques to a specific category were those described by Emerson and Colditz. The knowledge of bivariable techniques (standard reader) was established as the reference for the study of statistical access. Statistical use consisted in the tabulation of frequencies, graphic representations and chi square tests. RESULTS: The five most used categories were: Contingency tables, t and z tests, epidemiologic statistics, survival analysis (in both English journals) and analysis of variance (in both Spanish journals). The percentage of articles without statistics or with only descriptive statistics was 16% in Med Clin (Bare), 29% in Rev Clin Esp, 18% for in Lancet and 23% in the N Engl J Med. A reader familiarized with bivariable techniques has statistical access to 58% for the originals of Med Clin (Barc), 62% of Rev Clin Esp, 35% of the Lancet and 42% of the N Engl J Med. CONCLUSIONS: In the four journals selected, the use of bivariable techniques is still frequent although the growing use of multivariant analysis is of note. The study of the current profile of the standard reader in Spain is the aim of priority.

Note: Article RM Ripoll, Univ Barcelona, Fac Med, Dept Salut Publ & Legislacio Sanitaria, Unitat Biostat, Annex Fac Farm, E-08028 Barcelona, Spain

Keyword(s): REGRESSION MODELS

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