Quality of measures

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Reference no: EM13524390

TRUE / False Questions 

1. If all the members of a panel interview reach the same conclusion regarding a person who is being interviewed, it could be said that the interview ratings are reliable. 

2. Even when measurement error is present, scores can be measured with perfect precision. 

3. Error caused by failing to measure a key aspect of the attribute of interest (i.e., the attribute we wish to measure), is known as contamination error. 

4. Asking different questions of job applicants during comparisons of interview ratings between these same job applicants is an example of contamination error. 

5. If an attribute of job performance is "planning and setting work priorities," and the raters fail to rate people on that dimension during their performance appraisal, then the performance measure is contaminated. 

6. A measure with a coefficient alpha of .55 should generally be regarding as having adequate reliability. 

7. The standard error of measurement is a useful indicator of how accurate actual scores of applicants are in assessing the scores of a given measure. 

8. Reliability sets the lower limit on validity. 

9. The extent to which scores on a knowledge test truly reflect a job applicant's knowledge is a measure of the test's validity. 

10. Measuring the accuracy of a mechanical ability test in predicting the job performance of current employees involves a predictive validity design. 

11. Criterion measures are not used in the calculation of content validity. 

12. Even if methodological and statistical differences across criterion-related validation studies are not controlled for statistically, it is still probable that validity can be generalized from one specific situation to another. 

13. Organizations that collect assessment data need to attend to professional standards that govern their use. 

14. The process of criterion-related validation begins with the identification of criterion measures. 

15. The assessment of concurrent validity is more convenient and more efficient than the assessment of predictive validity. 

16. One guideline for effective staffing practice is that all predictors should be routinely subjected to content validation. 

17. Applicant flow statistics require the calculation of selection rates for groups and the subsequent comparison of those rates to determine if they are significantly different from each other. 

18. According to the Uniform Guidelines for Employee Selection Procedures (UGESP), comparisons of selection rates among groups should be based on the 70% rule. 

19. When assessing adverse impact, the law prohibits taking sample size into account. 

20. Investigation of applicant stock statistics is also known as "utilization analysis."

Reference no: EM13524390

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