Bias in Research

Following the line of interest in the previous post on Evidence-based Practise, I came across a review of research into bias in clinical medical research by Lise Lotte Gluud summarizing the findings of methodological studies on the influence of bias in clinical trials. There are many learnings here that could be applied to climate and environmental sciences in general.

It is recognized that uncontrolled observations can provide reliable evidence if the effects are dramatic. However, great care must be exercised when the effects are moderate or small, as such effects as errors, bias, spurious correlations, limit the value of uncontrolled observations. Computer models are essential where direct experiments are impossible. The main problem of experiments with models lies in extrapolation to situations without experimental testing (i.e. predictions), as these may lead to the wrong conclusions.

Thus the main concern of evidence-based practise is detecting and controlling research bias. One definition of bias is the unknown or unacknowledged error created during the design, measurement, sampling, procedure, or choice of problem studied.
Bias is so pervasive because we want to confirm our beliefs, even though science should be organized around proving itself wrong. The key difference between evidence-based and other research is the explicit attempt to eliminate sources of bias.

Selection Bias

Selection bias occurs when confounding factors are unevenly distributed between the experimental group and the control group. Selection bias is often called ‘cherry picking’, where only those data points with favorable outcomes are included in the experimental group. The medical field uses randomization to reduce such bias by creating control groups that are similar with regard to known confounding variables. For example, cores from trees selected for a dendrochronological study could include cores from a random sample of trees and subjected to parallel analysis. Climate analysis from a selected set of climate stations could include analysis of a random sample of stations.

Evaluation of models should be performed blind, where for example, the fit of climate models could be compared without the operators knowing which are the ‘real’ data, or what results were achieved by other models. Certain statistical methods such as logistic regression has been found to increase bias due to misclassification and measurement errors in confounding variables. So care should be taken in selecting methods that minimise inbuilt biases.


Medical science has regognized that the large randomized trial is one of our most reliable sources of evidence for assessment of intervention effects. As trials are not possible in the study of large systems such as climate, alternatives for capturing possible bias must be sought.

Adequate randomization requires that the results be uncertain (the ‘uncertainty principle’). If the result of a study is predetermined due to the study design or methodology, then bias compromises the results. Adequate randomization may be achieved by ‘monte carlo’ simulation, by the generation of random sequences and giving the random sequences and equal chance of producing the result.

Funding Bias

The effect of competing interests is debated in medical research. It has been found that industry funding has been associated with higher quality than trials without external funding. On the other hand, financial interests may bias the interpretation of trial results.

The reason for the association between funding and pro-industry conclusions include violation of the uncertainty principle, publication bias, and biased interpretation of trial results. The uncertainty principle means that there is demonstrated uncertainty about the results of the study. Violation of the uncertainty principle may be related to ‘cherry picking’ or flawed methodologies.

In 1997, approximately 16 percent of 1,396 highly ranked scientific journals had policies on conflicts of interest (78). Less than 1 percent of the articles published in these journals contained disclosures of personal financial interests. The importance of disclosure of financial interests is increasingly being recognized, as demonstrated by the following examples of publication bias and neglect of harm.

Publication Bias

Publication bias is the selective publication of the findings of trials with certain results, and may lead to exaggeration of effects. Medical studies have found that studies with statistically significant results were more likely to be published than studies with nonsignificant results, and they had significantly shorter times to publication.

Selective or delayed publication of the findings of studies with unwanted results seems to be a widespread but undocumented problem. For example, “The Scientific Consensus on Climate Change” by Nancy Oreskes found of 913 papers published between 1993 and 2003 with the words “global climate change” in their abstracts that “Not one of the papers refuted the claim that human activities are affecting Earth’s climate”. Although this was widly regarded as evidence of a consensus on global warming, a contribution from selection and publication bias is also highly likely.


In theory, evidence should be believed only if it is produced from well designed studies. Reviews of the medical literature suggest that most studies have variable randomization, small sample sizes and unclear control of bias. As the limitations of studies are frequently not addressed within the study, a systematic review of the evidence is necessary to identify limitations, such as bias or inadequate statistical power. Research on sources of bias is important to empirical fields. All methodological studies could benefit from the influence of better statistical designs.


0 thoughts on “Bias in Research

  1. Pingback: blog

  2. Pingback: my blog

  3. Pingback: great info

  4. Pingback: your blog

  5. Pingback: pokazy kulinarne

  6. Pingback: massage sexy paris 19

  7. Pingback: link url

  8. Pingback: Automotive

  9. Pingback: Online Business Idea

  10. Pingback: Car Zone CZX

  11. Pingback: Travel Insurance Reviews

  12. Pingback: makeanygirlwanttofuck

  13. Pingback: home

  14. Pingback: shopping

  15. Pingback: entertainment

  16. Pingback: technology

  17. Pingback: web

  18. Pingback: kliknij

  19. Pingback: important treatments

  20. Pingback: wnc humanists

  21. Pingback: Ryan Levin

  22. Pingback: filmiki erotyczne

  23. Pingback: this benefit

  24. Pingback: business lead solutions

  25. Pingback: Network Marketing

  26. Pingback: Home & Furniture

  27. Pingback: Sport Center

  28. Pingback: inilah harga terbaru

  29. Pingback: College Of Fashion and Design

  30. Pingback: automotive

  31. Pingback: Automotive Innovations

  32. Pingback: Shopping Safely Online

  33. Pingback: Automotive Zone

  34. Pingback: shopping

  35. Pingback: Dental Care Solutions

  36. Pingback: technology

  37. Pingback: technology

  38. Pingback: technology

  39. Pingback: business

  40. Pingback: entertainment

  41. Pingback: link do strony

  42. Pingback: finance

  43. Pingback: - pity 2015 program do pobrania

  44. Pingback: health

  45. Pingback: home improvement

  46. Pingback: home improvement

  47. Pingback: home improvement

  48. Pingback: home improvement

  49. Pingback: real estate

  50. Pingback: law

  51. Pingback: real estate

  52. Pingback: real estate

  53. Pingback: House & Home Renovation

  54. Pingback: real estate

  55. Pingback: travel

  56. Pingback: Education Management Program System

  57. Pingback: automotive

  58. Pingback: link do strony

  59. Pingback: Style Advice and Outfit Ideas

  60. Pingback: movie

  61. Pingback: music

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )


Connecting to %s