Literature DB >> 16505391

Bias in research studies.

Gregory T Sica1.   

Abstract

Bias is a form of systematic error that can affect scientific investigations and distort the measurement process. A biased study loses validity in relation to the degree of the bias. While some study designs are more prone to bias, its presence is universal. It is difficult or even impossible to completely eliminate bias. In the process of attempting to do so, new bias may be introduced or a study may be rendered less generalizable. Therefore, the goals are to minimize bias and for both investigators and readers to comprehend its residual effects, limiting misinterpretation and misuse of data. Numerous forms of bias have been described, and the terminology can be confusing, overlapping, and specific to a medical specialty. Much of the terminology is drawn from the epidemiology literature and may not be common parlance for radiologists. In this review, various types of bias are discussed, with emphasis on the radiology literature, and common study designs in which bias occurs are presented. Copyright RSNA, 2006.

Mesh:

Year:  2006        PMID: 16505391     DOI: 10.1148/radiol.2383041109

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  72 in total

1.  [Addiction counselling in the surgical emergency room. Implementation of a brief intervention for alcohol-intoxicated patients].

Authors:  J Röhrig; M Nafz; P C Strohm; J Bengel; T Hodel; S Wahl; M Berner
Journal:  Unfallchirurg       Date:  2013-07       Impact factor: 1.000

2.  Standardisation of liver MDCT by tracking liver parenchyma enhancement to trigger imaging.

Authors:  H Brodoefel; A Tognolini; G A Zamboni; S Gourtsoyianni; C D Claussen; V Raptopoulos
Journal:  Eur Radiol       Date:  2011-11-05       Impact factor: 5.315

Review 3.  The validation of screening tests: meet the new screen same as the old screen?

Authors:  Blase Gambino
Journal:  J Gambl Stud       Date:  2012-12

4.  Statistics in brief: how to assess bias in clinical studies?

Authors:  Jerome Lambert
Journal:  Clin Orthop Relat Res       Date:  2011-06       Impact factor: 4.176

5.  Posttraumatic growth after cancer: the importance of health-related benefits and newfound compassion for others.

Authors:  Bronwyn A Morris; Jane Shakespeare-Finch; Jennifer L Scott
Journal:  Support Care Cancer       Date:  2011-04-15       Impact factor: 3.603

6.  Statistics and methodology.

Authors:  Nancy A Obuchowski; Michael L Lieber
Journal:  Skeletal Radiol       Date:  2008-05       Impact factor: 2.199

7.  ECG-gated chest CT angiography with 64-MDCT and tri-phasic IV contrast administration regimen in patients with acute non-specific chest pain.

Authors:  Diana Litmanovich; Diana Litmanovitch; Giulia A Zamboni; Thomas H Hauser; Pei-Jan P Lin; Melvin E Clouse; Vassilios Raptopoulos
Journal:  Eur Radiol       Date:  2007-09-01       Impact factor: 5.315

8.  Why so few case reports--why (systematic) reviews instead?

Authors:  R Schulze
Journal:  Dentomaxillofac Radiol       Date:  2013-08-08       Impact factor: 2.419

9.  Six iterative reconstruction algorithms in brain CT: a phantom study on image quality at different radiation dose levels.

Authors:  A Löve; M-L Olsson; R Siemund; F Stålhammar; I M Björkman-Burtscher; M Söderberg
Journal:  Br J Radiol       Date:  2013-09-18       Impact factor: 3.039

10.  Treatment-related features improve machine learning prediction of prognosis in soft tissue sarcoma patients.

Authors:  Jan C Peeken; Tatyana Goldberg; Christoph Knie; Basil Komboz; Michael Bernhofer; Francesco Pasa; Kerstin A Kessel; Pouya D Tafti; Burkhard Rost; Fridtjof Nüsslin; Andreas E Braun; Stephanie E Combs
Journal:  Strahlenther Onkol       Date:  2018-03-20       Impact factor: 3.621

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