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Are interests a preference for particular work activities or outcomes?
Activities
Are values a preference for particular work activities or outcomes?
Outcomes
What are the 6 dimensions of structure of interests?
Investigative Artistic Social Enterprising Realistic Conventional
What are the 4 underlying dimensions of RIASEC
Data Ideas People Things
Are interests dimensions or types
Dimensions
Are opposite interests on the RIASEC correlated or uncorrelated
Uncorrelated
Work values
individual's characteristic pattern of preferences for certain work outcomes, goals, or objectives
Is the follow question asking about complementary or supplementary environment fit: does the environment meet the needs of the person?
Complementary
Is the follow question asking about complementary or supplementary environment fit: Do the person and environment share the same characteristics?
supplementary
What are two measures for assessing the environment?
People based measures Ratings
What interest measure predicts performance across all jobs
None
What is connected to performance as the major component of person-organization fit?
Values
Does the following question assess breadth or fidelity: how much of a job is captured by the assessment?
Breadth
Does the following question assess breadth or fidelity: How realistic are the materials?
Fidelity
What is required for a simulation to be valid?
Accurate behavioral responses
Are AC predictors usually combined clinically or mechanically?
Clinically
Are panel interviews more or less valid than structured interviews?
Less valid But more reliable
What is the relevant reliability for interviews?
interrater
Unstructured interviews have less construct validity for what dimensions?
Social skills and job experience
Do structured or unstructured interviews have stronger incremental validity?
Structured
What are unstructured interviews better for?
Recruiting applicants Choosing among a few equally good candidates
What is the drawback of empirical keying for biodata?
Some items will/won't correlate just by chance
What is the draw back of factor analytic for biodata
Items that group together are not necessarily good predictors
How can you improve factor analytic for biodata
Follow up factor analysis with other research
How do you improve empirical keying for biodata
Conduct multiple studies
How can you improve references?
Standardized use peer ratings
What is the following an example of: a female applicant is asked if she has any domestic responsibilities that might interfere with her work, but a male applicant is not asked that question
adverse/disparate treatment
What is the difference between adverse treatment and adverse impact?
Adverse treatment is intentional discrimination Adverse impact may not be intended discrimination
How is adverse impact shown?
Statistical disparities between a majority and a minority group in terms of outcomes
is the burden on the plaintiff or the defendant in an adverse impact case
plaintiff
What are the two things that a plaintiff has to show in an adverse impact case
1. belongs to a protected group 2. members of the protected group were statistically disadvantaged compared to the majority
What is the 80% rule used for
Adverse impact
a staffing model needs to be...
comprehensive
Why are compensatory selection systems important?
In most instances, humans are able to compensate for a relative weakness in one attribute through a strength in another one
What are the two basic ways to combine information in making a staffing decision
clinical and statistical
Is the hurdle system compensatory or noncompensatory?
non compensatory because the candidate could not continue unless the hurdle was cleared
cross validation
testing a multiple regression on a second sample to see if it still fits well
What are letter grades assigned to a score an example of?
Score banding
Standard error of measurement
amount of error in a test score distribution
What can we conclude if the difference between two candidates is less than the standard error of measurement?
candidates are not really different
Is subgroup norming legal or illegal
illegal
Are clinical or statistical methods preferable for layoffs?
statistical
Are mechanical or clinical predictions more accurate?
Mechanical
Is the following and example of mechanical, clinical, both, or synthesis of collection: personality or cognitive ability test score
mechanical
Is the following and example of mechanical, clinical, both, or synthesis of collection: expert rating of interview or simulation
clinical
Is the following and example of mechanical, clinical, both, or synthesis of collection: cognitive ability test scores and interview ratings
both
Is the following and example of mechanical, clinical, both, or synthesis of collection: take a prediction based on clinical judgment and combine it in a mechanical judgment
synthesis
Is the following and example of mechanical, clinical, both, or synthesis of collection: take a prediction based on mechanical combination and use it to inform a clinical judgement
synthesis
Is this a mechanical or clinical synthesis: clinical rating of the expert is treated as an additional predictor that is mechanically combined with all the other info to produce a final rating
mechanical synthesis
Is this a mechanical or clinical synthesis: predictor scores are combined using an equation based method to create a final composite score. The score is given to the expert and the expert combines all the info to their final rating
clinical synthesis
Can people do a good job of collecting data?
Yes
Can people do a good job of combining data?
No
Is clinical synthesis better than methods that are only equation based?
No
What is the most effective method for data combination?
mechanical
Why does clinical combination of data perform so poorly?
People are inconsistent about how they apple rules to making judgments Can by overly swayed by unusual/unimportant info develop incorrect rules for making judgments people have nice set of lawfully flawed decision making biases
What are the following an example of: optimal weights, meta analytic weights, research literature based weights
criterion weighting
What are the following an example of: criterion weighting, expert judgment based weights, bootstrapped weights
Differential weights
How do you get an optimal weight?
YOU CAN'T BITCHHHHH
What are the disadvantages of literature based weights
literature isn't as well organized as a good meta analysis results are likely to be less stable than a meta analysis
What are the advantages of using literature based weights
Useful if you're using predictors that have not been examined in a metaanalysis Weights based on solid empirical information Can use weights right away without waiting for a primary study
What is the problem with expert weights?
They are only as good as the experts we ask
Which is better: bootstrapped weights or the clinical judgments from which they are derived?
Bootstrapped
Are unit weights or differential weights better when predictors are of similar strength?
Unit weights
Are unit weights or differential weights better when predictors are very different?
Differential weights
What is the difference between fairness and bias?
Fairness is a subjective judgment referring to societal values about whether or not a decision is fair Bias is a technical concept concerned with whether a predictor score misrepresents a person's likelihood of effective future performance
In regards to bias, what is a major problem in using cognitive ability tests for selection?
There are subgroup differences in scores e.g. white mean score 1.0 higher htan black
What is the diversity-validity dilemma?
White-minority differences in cognitive ability scores make it impossible for organizations to both maximize the validity of their selection procedures and hire a diverse workforce
What subgroup differences are seen across sex?
Mostly none except psychomotor ability
What subgroup differences can be found across racial groups
General mental ability personality (but this is trivial)
What are three ways to evaluate bias?
mean score differences differential validity across groups differential prediction
What method for evaluating bias is the following: one group has a higher mean than another
mean score differences
What method for evaluating bias is the following: the predictor for whites is r=.30 but the predictor for blacks is r=.25
differential validity
What method for evaluating bias is the following: the intercept of the regression line for whites is higher than for blacks
Differential prediction
What is the limitation of differential validity
there is evidence of small differential validity across groups but no evidence of differential prediction
What do we see differences in validity across groups, but no evidence of differential prediction?
Differential prediction focuses on differences in unstandardized regression slopes and intercepts
What is the most used and legally defensible model of differential prediction
predictor oriented differential prediction
What happens if the a regression line for whites and regression line for blacks cross?
There is a significant interaction term between races

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