Literature DB >> 19260441

Statistical pitfalls in medical research.

V B Nyirongo1, M M Mukaka, L V Kalilani-Phiri.   

Abstract

In conducting and reporting of medical research, there are some common pitfalls in using statistical methodology which may result in invalid inferences being made. This paper is aimed to highlight to inexperienced statisticians or non-statistician some of the common statistical pitfalls encountered when using statistics to interpret data in medical research. We also comment on good practices to avoid these pitfalls.

Mesh:

Year:  2008        PMID: 19260441      PMCID: PMC3345655          DOI: 10.4314/mmj.v20i1.10949

Source DB:  PubMed          Journal:  Malawi Med J        ISSN: 1995-7262            Impact factor:   0.875


  16 in total

1.  Fallibility in estimating direct effects.

Authors:  Stephen R Cole; Miguel A Hernán
Journal:  Int J Epidemiol       Date:  2002-02       Impact factor: 7.196

2.  Statistical methods in clinical trials.

Authors:  Val J Gebski; Anthony C Keech
Journal:  Med J Aust       Date:  2003-02-17       Impact factor: 7.738

3.  Appropriate analysis and presentation of data is a must for good clinical practice.

Authors:  M Hayran
Journal:  Acta Neurochir Suppl       Date:  2002

4.  Quantifying biases in causal models: classical confounding vs collider-stratification bias.

Authors:  Sander Greenland
Journal:  Epidemiology       Date:  2003-05       Impact factor: 4.822

5.  Twenty statistical errors even you can find in biomedical research articles.

Authors:  Tom Lang
Journal:  Croat Med J       Date:  2004-08       Impact factor: 1.351

Review 6.  Subgroup analysis in clinical trials.

Authors:  David I Cook; Val J Gebski; Anthony C Keech
Journal:  Med J Aust       Date:  2004-03-15       Impact factor: 7.738

7.  Interaction: A word with two meanings creates confusion.

Authors:  Anders Ahlbom; Lars Alfredsson
Journal:  Eur J Epidemiol       Date:  2005       Impact factor: 8.082

8.  Confounding and effect-modification.

Authors:  O Miettinen
Journal:  Am J Epidemiol       Date:  1974-11       Impact factor: 4.897

9.  Control of confounding in the assessment of medical technology.

Authors:  S Greenland; R Neutra
Journal:  Int J Epidemiol       Date:  1980-12       Impact factor: 7.196

10.  Dichotomizing continuous predictors in multiple regression: a bad idea.

Authors:  Patrick Royston; Douglas G Altman; Willi Sauerbrei
Journal:  Stat Med       Date:  2006-01-15       Impact factor: 2.373

View more
  3 in total

Review 1.  A biomechanical sorting of clinical risk factors affecting osteoporotic hip fracture.

Authors:  Y Luo
Journal:  Osteoporos Int       Date:  2015-09-11       Impact factor: 4.507

2.  Hospital Readmission Risks Screening for Older Adult with Stroke: Tools Development and Validation of a Prediction.

Authors:  Jantra Keawpugdee; Pimpan Silpasuwan; Chukiat Viwatwongkasem; Plernpit Boonyamalik; Kwanjai Amnatsatsue
Journal:  Inquiry       Date:  2021 Jan-Dec       Impact factor: 1.730

3.  StatXFinder: a web-based self-directed tool that provides appropriate statistical test selection for biomedical researchers in their scientific studies.

Authors:  Aslı Suner; Gökhan Karakülah; Özgün Koşaner; Oğuz Dicle
Journal:  Springerplus       Date:  2015-10-22
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.