Detection bias is another word for surveillance bias, explained well here.
This article, “Selection Bias and Information Bias in Clinical Research,” describes the various types of selection bias, such as non-response bias, incidence-prevalence bias, loss-to-follow-up bias, volunteer bias and others.
The University of Oxford’s catalog of bias entry on Selection Bias offers multiple examples in plain language and the potential pitfalls of this bias.
This is a plain-language summary of confounding by indication, from the University of Oxford’s Catalogue of Bias, provides helpful diagrams for visualizing how this bias type can interfere with interpreting the relationship between exposures and outcomes.
A nice primer on confounding by indication at JAMA, this paper also discusses how to control for confounding by indication.
Post hoc analyses: To better understand the seductive attractiveness – and potential danger – of post hoc analyses, read Siddhartha Mukherjee’s excellent New York Times Magazine article “A Failure to Heal.” For a thoughtful exploration of how post hoc analyses can be helpful but also potentially misleading, and the various aspects of an analysis that should be considered in evaluating its validity, check out this article in the European Heart Journal, “Pre-specified vs. post-hoc subgroup analyses: are we wiser before or after a trial has been performed?”
A quick read on why double-blinded studies aren’t necessarily as “double-blinded” as they’re supposed to be: The Trouble With Double-Blind Placebo Studies
Attrition Bias from the University of Oxford Catalogue of Bias — Less detailed than other links on attrition bias, this page is quickly and easily skimmed on deadline for a nuts-and-bolts straightforward description of attrition bias and its potential consequences, plus links to examples.
“Attrition bias in randomized controlled trials” not only provides a good overview of what attrition bias is and why it’s a problem, but it also describes ways that attrition bias can be overcome. In speaking with researchers whose studies had substantial attrition, you could ask them what they did to account for that.
If you’re struggling to understand how — or how much — attrition bias can affect study findings, especially in randomized controlled trials, “Reporting attrition in randomised controlled trials” explains the effects and includes a sample trial with sample results as an example.
For a description of lead-time bias with a helpful diagram, check out this link from the Library of Medicine.
Some Effects of “Social Desirability” in Survey Studies
Social Desirability Bias and the Validity of Indirect Questioning
Recall Bias can be a Threat to Retrospective and Prospective Research Designs
Recall bias represents a major threat to the internal validity of studies using self-reported data. It arises with the tendency of subjects to report past events in a manner that is different between the two study groups. This pattern of recall errors can lead to differential misclassification of the related variable among study subjects with a subsequent distortion of measure of association in any direction from the null, depending on the magnitude and direction of the bias. Although recall bias has largely been viewed as a common concern in case-control studies, it also has been documented as an issue in some prospective cohort and randomized controlled trial designs.
How Do You Know Which Health Care Effectiveness Research You Can Trust? A Guide to Study Design for the Perplexed: An article in Preventing Chronic Disease, by Stephen B. Soumerai et al. on June 25, 2015, reviews different types of common bias in studies based on study design, such as healthy user bias, history bias and social desirability bias.
Varieties of bias to guard against: This PDF from MedicalBiostatistics.com gives an extensive overview of 32 different types of bias that can occur in medical research publishing. It is impossible to design a study that contains no bias at all, but there are ways to minimize bias, which this document discusses as well.
Bias in randomized controlled trials: This is a sample chapter from a book which explains the types of bias that can specifically occur in randomized controlled trials. It is a little long, but it’s written in layperson terms with clear subtitles and sections that make it highly readable and accessible.