Literature DB >> 15010353

Ten categories of statistical errors: a guide for research in endocrinology and metabolism.

Tyson H Holmes1.   

Abstract

A simple framework is introduced that defines ten categories of statistical errors on the basis of type of error, bias or imprecision, and source: sampling, measurement, estimation, hypothesis testing, and reporting. Each of these ten categories is illustrated with examples pertinent to research and publication in the disciplines of endocrinology and metabolism. Some suggested remedies are discussed, where appropriate. A review of recent issues of American Journal of Physiology: Endocrinology and Metabolism and of Endocrinology finds that very small sample sizes may be the most prevalent cause of statistical error in this literature.

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Year:  2004        PMID: 15010353     DOI: 10.1152/ajpendo.00484.2003

Source DB:  PubMed          Journal:  Am J Physiol Endocrinol Metab        ISSN: 0193-1849            Impact factor:   4.310


  5 in total

1.  Methodological improvement of publications in the JIMD. Better is the enemy of good--Voltaire.

Authors:  Peter Burgard
Journal:  J Inherit Metab Dis       Date:  2010-08       Impact factor: 4.982

Review 2.  Challenging a dogma of exercise physiology: does an incremental exercise test for valid VO 2 max determination really need to last between 8 and 12 minutes?

Authors:  Adrian W Midgley; David J Bentley; Hans Luttikholt; Lars R McNaughton; Gregoire P Millet
Journal:  Sports Med       Date:  2008       Impact factor: 11.136

3.  Systematic survey of the design, statistical analysis, and reporting of studies published in the 2008 volume of the Journal of Cerebral Blood Flow and Metabolism.

Authors:  Hanna M Vesterinen; Hanna V Vesterinen; Kieren Egan; Amelie Deister; Peter Schlattmann; Malcolm R Macleod; Ulrich Dirnagl
Journal:  J Cereb Blood Flow Metab       Date:  2010-12-15       Impact factor: 6.200

4.  Bias in research.

Authors:  Ana-Maria Simundić
Journal:  Biochem Med (Zagreb)       Date:  2013       Impact factor: 2.313

5.  Metabolomics analysis identifies different metabotypes of asthma severity.

Authors:  Stacey N Reinke; Héctor Gallart-Ayala; Cristina Gómez; Antonio Checa; Alexander Fauland; Shama Naz; Muhammad Anas Kamleh; Ratko Djukanović; Timothy S C Hinks; Craig E Wheelock
Journal:  Eur Respir J       Date:  2017-03-29       Impact factor: 33.795

  5 in total

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