K E Kotliar1, I M Lanzl2. 1. Fachbereich Medizintechnik und Technomathematik, Fachhochschule Aachen, Campus Jülich, Heinrich-Mussmann-Str. 1, 52428, Jülich, Deutschland. kotliar@fh-aachen.de. 2. Augenklinik, Klinikum rechts der Isar, Technische Universität München, 80333, München, Deutschland.
Abstract
BACKGROUND: The use and the understanding of statistics are very important for biomedical research and for the clinical practice. This is particularly true for estimation of the possibilities for different diagnostic and therapy options in the field of glaucoma. The apparent complexity and contraintuitiveness of statistics along with a cautious acceptance by many physicians, might be the cause of conscious and unconscious manipulation with data representation and interpretation. OBJECTIVES: Comprehendable clarification of some typical errors in the handling of medical statistical data. MATERIALS AND METHODS: Using two hypothetical examples from glaucoma diagnostics the presentation of the effect of a hypotensive drug and interpretation of the results of a diagnostic test and typical statistical applications and sources of error are analyzed in detail and discussed. RESULTS: Mechanisms of data manipulation and incorrect data interpretation are elucidated. Typical sources of error in the statistical analysis and data presentation are explained. CONCLUSION: The practical examples analyzed demonstrate the need to understand the basics of statistics and to be able to apply them correctly. The lack of basic knowledge or half-knowledge in medical statistics can lead to misunderstandings, confusion and wrong decisions in medical research and also in clinical practice.
BACKGROUND: The use and the understanding of statistics are very important for biomedical research and for the clinical practice. This is particularly true for estimation of the possibilities for different diagnostic and therapy options in the field of glaucoma. The apparent complexity and contraintuitiveness of statistics along with a cautious acceptance by many physicians, might be the cause of conscious and unconscious manipulation with data representation and interpretation. OBJECTIVES: Comprehendable clarification of some typical errors in the handling of medical statistical data. MATERIALS AND METHODS: Using two hypothetical examples from glaucoma diagnostics the presentation of the effect of a hypotensive drug and interpretation of the results of a diagnostic test and typical statistical applications and sources of error are analyzed in detail and discussed. RESULTS: Mechanisms of data manipulation and incorrect data interpretation are elucidated. Typical sources of error in the statistical analysis and data presentation are explained. CONCLUSION: The practical examples analyzed demonstrate the need to understand the basics of statistics and to be able to apply them correctly. The lack of basic knowledge or half-knowledge in medical statistics can lead to misunderstandings, confusion and wrong decisions in medical research and also in clinical practice.
Entities:
Keywords:
Median; Prevalence; Sensitivity; Specificity; Statistical data interpretation
Authors: Malcolm R Macleod; Aaron Lawson McLean; Aikaterini Kyriakopoulou; Stylianos Serghiou; Arno de Wilde; Nicki Sherratt; Theo Hirst; Rachel Hemblade; Zsanett Bahor; Cristina Nunes-Fonseca; Aparna Potluru; Andrew Thomson; Julija Baginskaite; Julija Baginskitae; Kieren Egan; Hanna Vesterinen; Gillian L Currie; Leonid Churilov; David W Howells; Emily S Sena Journal: PLoS Biol Date: 2015-10-13 Impact factor: 8.029