Chapter 9 analyzing bias and assuring fairness p206
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Chapter 9 Analyzing Bias and Assuring Fairness p206. Unfair Discrimination Item & Test Bias Test-Score Banding. Bias defined “Systematic group differences in item responses, test scores, or other assessments for reasons unrelated to the trait.” Cultural bias defined

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Chapter 9 Analyzing Bias and Assuring Fairness p206

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Chapter 9 analyzing bias and assuring fairness p206

Chapter 9 Analyzing Bias and Assuring Fairness p206

  • Unfair Discrimination

  • Item & Test Bias

  • Test-Score Banding

Chapater 9 Analyzing Bias and Assuring Fairness


Chapter 9 analyzing bias and assuring fairness p206

  • Bias defined

    • “Systematic group differences in item responses, test scores, or other assessments for reasons unrelated to the trait.”

  • Cultural bias defined

    • “ if an acceptable response depends on skills or information common in one culture but not in the other.”

  • Discrimination defined

    • “Making distinctions”

      • – not same as unfair discrimination

    • Define “unfair” discrimination

    • What’s the differences between the two –give an example

Chapater 9 Analyzing Bias and Assuring Fairness


Discrimination

DISCRIMINATION

  • Discrimination Based on Group Membership

    • Protected groups

      • Race

      • Color

      • Religion

      • Gender

      • Nat’l origin

      • LGBT?

Chapater 9 Analyzing Bias and Assuring Fairness


Distributional differences

Distributional Differences

Group Mean Differences (Give an example for each below)

  • Two groups are biased samples (from respective populations)

    E.g. extensive uncritical recruiting for lower scoring group

    Would not be biased(why not?)

  • Two groups are representative (not biased if actually differ on the trait)

  • Test items require experiences not common to lower scoring group (not biased if experiences required)

  • Test administration conditions differ for the two groups

Chapater 9 Analyzing Bias and Assuring Fairness


Racial differences in iq

Racial Differences in IQ

  • Few believe there are no race differences

    • Means for:

      • East Asians 105

      • Europeans (Whites) 100

      • Blacks 85

    • Cohen effect size

      • Hispanics .6 to .8 SD < Whites

      • Blacks 1 SD <Whites

  • Many argue about the causes

  • Predictability of IQ for is comparable for blacks and whites

Chapater 9 Analyzing Bias and Assuring Fairness


Race differences in iq furnham 08 p 207

Race Differences in IQ (Furnham ’08, p 207)

  • Three plausible explanations

    • Evidence of biological & genetic differences between races

    • Evidence of sociocultural, economic & political forces for differences

      -distinct from racial characteristics

      -But confounded with them

    • Differences are only artifacts of test design, administration, or measurement

      -no real differences

Chapater 9 Analyzing Bias and Assuring Fairness


Black white racial differences in iq

Black-White Racial Differences in IQ

  • Greater variation within groups than between

    • 16% Blacks score above the White mean

    • For a cutoff of 70 score for special education

      • There will be 1 White for every 7 Blacks

    • Black/White differences are constant over time and life span

    • Differences are present prior to school entry

    • Differences are not constant for diff types of measures of intelligence

Chapater 9 Analyzing Bias and Assuring Fairness


Black white differences in iq implications for workforce gottfredson 2002

Black & White Differences in IQ(implications for workforce) Gottfredson (2002)

  • 22% Whites & 59% of Blacks have IQ < 90

    • Considerably fewer Blacks (proportionately) are competitive for mid-level jobs:

      • fire fighting, skilled trades, many clerical jobs

        • Mean IQ is about 100 (1 SD above Whites)

        • 80 is the threshold for being competitive in lowest level jobs

          • 4 times as many Blacks (30%) cf Whites (7%) fall bellow that threshold

Chapater 9 Analyzing Bias and Assuring Fairness


Implications for black white iq differences

Implications for Black / White IQ Differences

  • On the higher end of the distribution (IQ =125)

    • Score of 125 = mean for professionals (e.g. lawyers, physicians, engineers, high-level executives etc.)

  • Black / White ratio is only 1:30 at this level

  • Conclusion: Disparate impact

    • with legal and political tension…

    • Is “particularly acute in the most complex, most socially desirable jobs” (Gottfredson, ’02, p. 41).

Chapater 9 Analyzing Bias and Assuring Fairness


Chapter 9 analyzing bias and assuring fairness p206

  • Differences in Other Distributional Characteristics (table 9.1 p211)

    • Note: group means are different, but variability is greater

      • At lower selection ratios, differences in proportions may disappear.

  • Discrimination as Systematic Measurement Error

    • If discrimination error is systematic and more for one group than the other (e.g. test taking habits)

    • can be unfair even if not illegal

  • Chapater 9 Analyzing Bias and Assuring Fairness


    Analysis of bias and adverse impact in test use

    ANALYSIS OF BIAS AND ADVERSE IMPACT IN TEST USE

    • Test bias

      • Unwanted sources of variance in scores from different groups

  • Adverse impact

    • Social, political or legal term (effects of test use)

  • Chapater 9 Analyzing Bias and Assuring Fairness


    Analysis of bias and adverse impact in test use1

    ANALYSIS OF BIAS AND ADVERSE IMPACT IN TEST USE

    • Test Bias as Differential Psychometric Validity

      • Bias = “when groups matched on the trait have different scores because of one or more sources of variances related to group membership”

        • It is the “Meaning inferred” from scores may or may not be biased (Not the test itself)

        • It is group related (not just for a single individual)

        • Groups must be assumed to be equal on the trait

        • Definition emphasizes sources of group variances (potentially identifiable) (not on group means)

          -e.g. “stereotype threat” (Steele & Aronson, ‘95)

    Chapater 9 Analyzing Bias and Assuring Fairness


    Analysis of bias and adverse impact in test use2

    ANALYSIS OF BIAS AND ADVERSE IMPACT IN TEST USE

    • Adverse Impact (legal term, not statistical)

      • Mean differences alone do not indicate bias

        • How does this “attitude problem” force adversarial roles?

        • What’s a better term?

      • Adverse impact reasons:

        • Chance (not due to bias)

        • Measurement problems

        • Nature of test use

        • Differences in distribution sizes

        • Reliable sub-group approaches to test taking

        • True population differences in trait (not due to bias)

    • NOTE TABLE 9.2 P 216

    • Criterion Bias (criterion must be valid)

    Chapater 9 Analyzing Bias and Assuring Fairness


    Differential item functioning dif

    DIFFERENTIAL ITEM FUNCTIONING(DIF)

    • DIF preferred over ‘bias’

      • “Simple minded item difficulty statistics”

        • You can’t consider the item itself (dependent upon the trait distribution –thus confounded with it)

      • Court cases:

        • Golden Rule Insurance Company v. Washburn (‘84)

          • Mandated that group item difficulty could not differ by more than .15!!

        • Allen v. Alabama State Board of Education (‘85)

          • More restrictive – not more than .05 max difference!!!

    Chapater 9 Analyzing Bias and Assuring Fairness


    Acting on the findings

    ACTING ON THE FINDINGS

    • Corrective Actions (4) Under the Uniform Guidelines – p 218

      • Should we maximize the criterion performance or avoid the appearance of discriminatory practice?

      • To ease tensions how should the Ferguson police dept deal with the imbalance in B &W police officers as it reflects the population’s racial mix?

    • Score Adjustments

      • Race norming in U.S . Employment Service (GATB)

        • Scores of Hispanics, Blacks and Whites were %ile ranks within groups

        • What effect did this have ?

      • Employment Quotas

        • USTES

        • Are quotas acceptable in other countries?

    Chapater 9 Analyzing Bias and Assuring Fairness


    Analysis of bias con t

    Analysis of Bias (con’t)

    • “Ranges of Indifference” in Test Score Bands

      • Band Width

        • They exist whatever you do…so how to decide?

        • Standard error of the difference in scores (sd= sm √ 2 )

        • Adjustment in band with should be based on judgments re: loss of utility

      • Decisions Within Bands

      • Fixed Bands (don’t slither down)

      • Sliding Bands (slither down)

      • Rubber Bands

        • What are these used for?

    Chapater 9 Analyzing Bias and Assuring Fairness


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