hra 310 chapter 7

14
Chapter Seven Measurement and Decision-Making Issues in Selection

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Page 1: Hra 310 chapter 7

Chapter Seven

Measurement and Decision-Making

Issues in Selection

Page 2: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–2

Chapter Outline

• Statistical Methods in Selection• Reliability• Validity• Decision Making in Selection• Utility of a Selection System

Page 3: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–3

The Selection Process

• Measurement– Ensuring that selection tests are reliable

and valid• Decision making

– Combining information about a person to make hiring decision

• Evaluation– Making sure hiring decisions increase firm

efficiency and profitability

Page 4: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–4

Statistical Methods in Selection

• Correlation Analysis– Degree of linear relationship between

variables– Commonly measured by the Pearson

product moment correlation coefficient• Regression Analysis

– Best fitting line equation

Page 5: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–5

Reliability

• Consistency of measurement• Systematic Error versus Random Error• Methods of Measuring Reliability

– Test-Retest– Interrater Reliability– Internal Consistency

Page 6: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–6

Validity

• Content Validity– Are items a representative sample– Based on job analysis– Determined by judgment of job experts– Lawshe method

Page 7: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–7

Validity (cont’d)

• Criterion-Related Validity – does a selection test adequately predict an outcome– Concurrent Validation

• Current employees• Predictor and criterion measured at same time• Problem = respresentativeness of sample• Problem = restriction of range

Page 8: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–8

Validity (cont’d)

• Predictive Validation– Job applicants– Predictor measured (time 1)– Applicants hired without predictor influence– Criterion measured (time 2)– Problem = sample size needed– Problem = time between T1 and T2

Page 9: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–9

Special Concerns in Validity

• Test Fairness– Mean differences in test scores– Equitable treatment– Differential prediction– Differential validity

• Validity Generalization

Page 10: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–10

Decision Making in Selection

• Additive Models– Higher score = better score– Compensatory model

• Multiple Cutoff– Minimum score for each test– Non-compensatory model

• Multiple Hurdle– Sequential testing– Minimum score for each test– Non-compensatory model

Page 11: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–11

Decision Making (cont’d)

• Profile Matching– Ideal pattern of scores

• Adjusting Test Scores of Minority Group Members– In most cases illegal– Fixed bands– Sliding bands

Page 12: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–12

Utility of a Selection System

• Efficiency of Selection• Types of selection decisions

– Quadrant A: True-Positive Decisions– Quadrant B: False-Negative Decisions– Quadrant C: True-Negative Decisions– Quadrant D: False-Positive Decisions

Page 13: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–13

Utility (cont’d)

• Selection Efficiency Is Affected By:– Validity– Selection Ratio– Base Rate of Success

• Taylor-Russell Tables– Standard Deviation of Performance in

Dollars– Costs Associated with Selection

Page 14: Hra 310 chapter 7

Copyright © Houghton Mifflin Company. All rights reserved. 7–14

Review

• Statistical Methods in Selection• Reliability• Validity• Decision Making in Selection• Utility of a Selection System