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Related Concept Videos

Bias01:22

Bias

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Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
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Confirmation Biases01:31

Confirmation Biases

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The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
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Stereotypes, Prejudice, and Discrimination02:55

Stereotypes, Prejudice, and Discrimination

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Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
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In- and Out-Groups01:31

In- and Out-Groups

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People all belong to a gender, race, age, and social economic group. These groups provide a powerful source of our identity and self-esteem (Tajfel & Turner, 1979) and serve as our in-groups. An in-group is a group that we identify with or see ourselves as belonging to.
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Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

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Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
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Groupthink01:34

Groupthink

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When in group settings, we are often influenced by the thoughts, feelings, and behaviors around us. Groupthink is another phenomenon of conformity where modification of the opinions of members in a group aligns with what they believe is the group consensus (Janis, 1972). In such situations, the group often takes action that individuals would not perform outside the group setting because groups make more extreme decisions than individuals do. Moreover, groupthink can hinder opposing trains of...
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Bias--is it a problem, and what should we do?

Ian R Dohoo1

  • 1Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PEI C1A 4P3, Canada.

Preventive Veterinary Medicine
|November 2, 2013
PubMed
Summary
This summary is machine-generated.

Veterinary epidemiologists effectively manage random error but often overlook systematic error in observational studies. Addressing systematic errors like confounding and bias is crucial for accurate research findings.

Keywords:
BiasConfoundingMisclassification biasQuantitative bias adjustmentSelection biasSystematic error

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Area of Science:

  • Veterinary epidemiology
  • Observational study methodology

Background:

  • Observational studies are susceptible to random and systematic errors.
  • Random error is reducible by increasing sample size, while systematic error stems from study design or data collection issues.
  • Veterinary epidemiology has advanced in managing random error but needs more focus on systematic error.

Purpose of the Study:

  • To highlight the importance of addressing systematic errors in veterinary observational studies.
  • To discuss sources and impacts of systematic errors, including unmeasured confounders, selection bias, and information bias.
  • To present methods for managing systematic errors in epidemiological research.

Main Methods:

  • Review of common sources of systematic error in observational studies.
  • Discussion of the unpredictable nature and potential impact of various biases.
  • Exploration of strategies for mitigating systematic errors, such as bias analysis.

Main Results:

  • Systematic errors, including unmeasured confounding, selection bias, and information bias, can significantly impact study results.
  • The direction and magnitude of bias are not always predictable.
  • Qualitative and quantitative bias analyses are key methods for addressing these errors.

Conclusions:

  • There is a need for greater attention to systematic error in veterinary epidemiology.
  • Methods exist to assess and manage systematic errors, improving the validity of observational studies.
  • Incorporating bias assessment strengthens the reliability of epidemiological findings.