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Chapter Nine

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Title: Chapter Nine


1
Chapter Nine
  • Understanding Bias

2
The Nature of Bias
  • Research bias may be thought of as a preference
    or predisposition to favour a particular outcome
    thus indicating a systematic distortion of
    research conclusions
  • Typically the distortions are inadvertent, but
    they can also be intentional
  • If bias is not addressed ina study, the
    reliability of findings is considered suspect

3
Bias in Quantitative Research
  • Bias implies there is an unknown truth waiting to
    be described
  • In quantitative designs the approach suggests
    that the researcher knows the truth simply
    wants to confirm his/her knowledge
  • eg. Questionnaire responses reflect the
    researchers previous knowledge, values, etc.

4
Bias in Qualitative Research
  • In qualitative research the researcher is an
    integral part of the research design the
    participants world
  • To minimize bias in qualitative designs the
    researcher incorporates it into the design by
  • bracketing
  • audit trail
  • selecting unfamiliar participants
  • selecting a topic that is not too close to the
    researcher on a personal level

5
Triple Biases Nursing, Science, Culture...
  • We take our nursing predispositions with us to
    our research projects
  • We tend to seek corroboration of our
    preconceptions, helps to make sense of a
    complicated world, reaffirms our pet theories
  • Science itself potentially blinds researchers
    because of the expectations of findings, the
    belief in certain theories. Like culture, science
    produces blinders

6
Sexism A Form of Bias
  • Sexism is discrimination on the basis of gender
  • RCTs used mainly by medicine have made women
    victims of this approach, studying women mainly
    as objects, ignoring their needs experiences

7
Types of Sexism in Research
  • Androcentricity (male perspective)-based on
    individualism, materialism, competitiveness -
    in contrast to the views of women, ethnic groups,
    the poor who focus on family concerns rather
    than themselves
  • Overgeneralization overspecificity
  • Gender Insensitivity
  • Familism - treating family as unit of analysis,
    rather than the individual

8
Sources of Bias...
  • need to design studies to systematically test
    alternative explanations
  • researcher affect refers to the bias that results
    from a researcher having fallen in love with some
    pet theory or explanation

9
Bias Selection of Problem
  • Some things judged more important by funding
    agencies, ones discipline peers
  • bias is toward the conventional, standard
    projects the selection of variables
    conventionally considered important the
    exclusion of those conventionally considered
    unimportant
  • probably still a bias toward quantitative
    approaches

10
Bias Sampling Design
  • results may be distorted by choosing to study
    sub-populations with known slants
  • attitudes toward abortion in an urban community
    with a free standing abortion clinic vs rural
    communities
  • bias is problematic in studies where the sample
    self-selects to participate

11
Bias Funding
  • SSHRC main funding for social science research
  • special funding available in hot areas
  • traditional areas better funding
  • NSERC and CIHR are better funded
  • research in a social context

12
Bias Data Collection
  • Experimenter effect reference is to the
    influence of experimenter preferences and
    expectations
  • Robert Rosenthal the smart rats study.
  • Clever Hans
  • Expectancy
  • Demand characteristics

13
Bias Data Analysis
  • Coding Errors
  • Random Error
  • Systematic Error
  • Data Massaging
  • Hunting

14
Bias Reporting of Findings
  • T.D. Sterling, 1959, 1995. Notes the problem of
    journals publishing only statistically
    significant findings.

15
Bias Funding
  • Possibility of funding agencies to determine what
    is important to know have they got it right?
  • Problems of emerging disciplines in competing
    with established ones

16
Advocacy Versus Pure Research
  • P. 313.
  • Mainstream research supportive of established
    interests in society. Is there a legitimate
    place to support the interests of minorities,
    women, people with disabilities, the working
    poor, the homeless

17
Rules for Minimizing Bias
  • Education
  • Avoid Sexism
  • Advocacy or Explanation?
  • Descriptive Accuracy
  • Let disconfirmation be your guide
  • Policy Recommendations are Value Based
  • Be skeptical of Research Findings

18
Rules Cont
  • Read Literature Cautiously, Skeptically
  • Distinguish Advocacy from Pure Research
  • Use Theory to Generate Testable Hypotheses
  • Be Sensitive to your own outcome preferences
  • Do not disclose hypotheses to subjects or
    assistants

19
Rules Cont.
  • Be Accepting of All Responses
  • Specify Data Analysis Procedures in Advance
  • Check for Random Systematic Errors
  • Report any Data Massaging
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