1. Topic #5: Selection Theory
Paul L. Schumann, Ph.D.
Professor of Management
MGMT 440: Human Resource Management
© 2008 by Paul L. Schumann. All rights reserved.

2. Outline Selection in HR Selection Process Review of Correlation
Criteria for Selection Methods
Using Selection Methods
Utility Analysis
Taylor-Russell Table
Decision-Making in Selection

3. Predicted Job Performance of Each Applicant
Selection in HR
Selection is the HR term for hiring
Problem: we don’t know the applicant’s job performance until after we hire the applicant
Solution: we need to predict the applicant’s job performance
Selection methods: the predictors of job performance used to make the selection decision
Examples of selection methods: résumé evaluations, employment interviews, tests of various KSAs, …
Selection Methods (Predictors of Job Performance)
Predicted Job Performance of Each Applicant
Selection Decision (Positive or Negative: Hire or Don’t Hire)

4. Predicted Job Performance of Each Applicant
Selection in HR
Selection Methods (Predictors of Job Performance)
Predicted Job Performance of Each Applicant
Selection Decision (Positive or Negative: Hire or Don’t Hire)
We use the selection methods (which are measures of the applicant’s qualifications) to predict the job performance of each applicant to make the selection decision
Positive selection decision: Hire the applicant if we predict the applicant will have good job performance
Negative selection decision: Don’t hire the applicant if we predict the applicant will have poor job performance

5. Selection Process
Step 1 Measurement: Measure each applicant’s qualifications using the selection methods
Use “good” selection methods: reliable & valid
Step 2 Decision Making: Use the qualifications to predict job performance to decide which applicant to hire
Step 3 Evaluation: Evaluate the selection process
Continuous improvement of management processes
Source of figure: Fisher, Schoenfeldt, & Shaw (2006), Figure 7.1, p. 283

6. Review of Correlation
Correlation measures the degree of relationship between 2 variables
Example: What is the relationship (correlation) between the job interview & job performance?
Do applicants who do better on the interview also do better on the job?
Strong correlation means the job interview accurately predicts job performance
Use the job interview as a selection method
Weak correlation means the job interview does not predict job performance
Don’t use the job interview as a selection method

7. Review of Correlation (more)
Correlation range: −1.0  0.0  +1.0
Sign denotes the direction of the relationship between the 2 variables
r > 0: positive relationship
r = 0: no relationship
r < 0: negative relationship
Magnitude denotes the strength of the relationship
r = 1.0: perfect prediction
Example: correlation = r = 0.677

8. 2 Criteria for Selection Methods
1. Reliability: consistency of measurement
Does the measuring tool give us the same measurement every time we measure the same thing?
Example: a reliable ruler vs. an unreliable ruler
Example: a reliable programming skills test?
2. Validity: Does the measuring tool measure what we really want to measure?
Example: Is a ruler a valid measure of temperature? No.
Example: Is the programming skills test a valid predictor of job performance of computer programmers? Maybe.

9. Criteria 1: Reliability
Reliability: consistency of measurement
3 methods of determining reliability:
1. Test-retest reliability: measure the same thing twice
Example: Give the programming skills test to people (applicants or employees) twice and correlate their scores
2. Inter-rater reliability: see if 2 raters agree in their ratings
Example: Have 2 interviewers witness job interviews, each interviewer rates each applicant, then correlate the ratings
3. Internal consistency reliability: “coefficient alpha”
Example: Programming skills test

10. Criteria 1: Reliability (more)
Example of test-retest reliability
Delta Intelligence Test (DIT = [0  50])
Give current employees the DIT twice: DIT1 & DIT2
Put the DIT scores into an Excel spreadsheet or SPSS database
Reliability Coefficient: Correlate DIT1 & DIT2

11. Criteria 1: Reliability (more)

12. Criteria 2: Validity
Validity: Are we measuring what we want to measure?
3 methods of determining validity:
1. Content validity: Judge if the content of the selection method is a good match with the content of the job
Example: Are the questions on the programming skills test asking about programming skills that are used on the job?
Example: The questions on the test are mostly about writing programs in COBOL while the job uses C++ and Java
Based on the mismatch of the content of the test versus the content of the job, we might judge the programming skills test to have poor validity for our purposes

13. Criteria 2: Validity (more)
3 methods of determining validity (more):
2. Criterion-related concurrent validity:
Measure 2 things at the same time (concurrently):
Selection method (predictor of job performance)
Example: Programming skills test
Job performance
Example: Job performance ratings of programmers
Use our current employees as our sample (we don’t observe the concurrent job performance of the applicants)
Example: Use our current programmers — give them the test
Correlate selection method scores with job performance ratings

14. Criteria 2: Validity (more)
3 methods of determining validity (more):
3. Criterion-related predictive validity:
Measure 2 things at different times:
Measure now: Selection method (predictor of job performance)
Example: Programming skills test
Measure in the future: Job performance
Example: Job performance ratings of programmers
Use the applicants we hire as our sample
Example: Give applicants the test, keep scores on file
Correlate selection method scores with job performance ratings after the new hires have been on the job for a while

15. Criteria 2: Validity (more)
Example of criterion-related concurrent validity:
Delta Intelligence Test
Give current employees the DIT
Put the DIT scores (DIT2) into an Excel spreadsheet or SPSS database with job performance ratings (Perf)
Validity Coefficient: Correlate DIT2 & Perf

16. Criteria 2: Validity (more)

17. Using Selection Methods
Terminology:
Selection cut-off score: minimum passing score on a selection method
Job performance cut-off score: minimum acceptable level of job performance
Selection ratio (SR) = % of applicants hired = # hired / # applicants
Base rate of success (BRS) = % of applicants who would have acceptable job performance if they were hired = # acceptable job performance / # applicants

18. Using Selection Methods (more)
Terminology (more):
True positive: applicant is hired and turns out to have acceptable job performance
Correct decision: we hired a good employee
False positive: applicant is hired and turns out to have unacceptable job performance
Mistake: we hired a poor performing employee (a dud)
False negative: applicant is not hired, but would have had acceptable job performance if hired
Mistake: we missed hiring a good person
True negative: applicant is not hired, and if had been hired would have had unacceptable job performance
Correct decision: we avoided hiring a dud

19. Using Selection Methods (more)
Example: Criterion-related concurrent validity Employee Performance Rating Scale: 7 = truly exceptional 6 = excellent 5 = very good 4 = good 3 = satisfactory 2 = unsatisfactory 1 = very unsatisfactory Validity coefficient = r = Performance cut-off = 3 Selection cut-off = 22
False Negatives
True Positives 29 64 4 3
True Negatives
False Positives
SR = 67%

20. Using Selection Methods (more)
Cost of making a false positive selection error (cost of hiring a “dud”):
Recruiting & selection costs
Orientation & training costs
Performance appraisal costs
Costs associated with poor job performance
Termination costs
Costs of hiring a replacement
Repeat recruiting & selection, orientation & training, etc.

21. Using Selection Methods (more)
Cost of making a false negative selection error (cost of failing to hire an applicant who would have good job performance):
Recruiting & selection costs
Opportunity costs: cost of letting good talent slip through our fingers
Costs associated with needing a bigger pool of applicants
Increases recruiting & selection costs

22. Using Selection Methods (more)
What can we do to manage the costs associated with both types of selection mistakes?
Change our hiring standards
Raise our hiring standards: raise the selection cut-off score
Example: raise the minimum passing score on the DIT
Lower our hiring standards: lower the selection cut-off score
Change which selection methods we use
Switch from a less valid selection method to a more valid selection method
Switch from a more valid selection method to a less valid selection method

23. Using Selection Methods (more)
Example:  selection cut-off score from 22 to 26:
 false positives (hire fewer duds): 3 → 0 (costs down)
 false negatives (reject more good people): 29 → 64 (costs up)
 SR (we hire a smaller percentage of the applicant pool, so we’ll need a bigger pool): 67% → 29% (hiring costs up)
Some costs down, up
False Negatives
True Positives 64 29 7
True Negatives
False Positives
SR = 29%

24. Using Selection Methods (more)
Example:  validity (switch to a selection method that has higher validity than the DIT) :
 false positives (hire fewer duds: costs down)
 false negatives (reject fewer good people: costs down)
But is the more valid selection method more expensive?
If a selection method has perfect validity (r = 1.0), then no selection errors
False Negatives
True Positives 29 64 4 3
True Negatives
False Positives
SR = 67%

25. Utility Analysis We see that there are tradeoffs to be analyzed
If we raise our hiring standards (raise the selection cut-off score), there are:
Fewer false positives: we hire fewer duds (costs go down)
More false negatives: more good talent slips away (costs go up)
Selection ratio goes down: we reject more applicants, and so need a bigger pool of applicants (costs go up)
If we switch to a more valid selection method, there are:
Fewer false negatives: less good talent slips away (costs go down)
The more valid method might be more expensive (costs go up)

26. Utility Analysis (more)
Goal of utility analysis: Determine the value of the selection system or of changes in the selection system
Utility analysis is a method of cost-benefit analysis
“Value” is measured in money terms
How does the current selection system add value to the organization?
How would changes to the selection system add value to the organization?
Example: Evaluate the effect of changing our hiring standards
Example: raise the selection cut-off score
Example: Evaluate the effect of switching selection methods
Example: switch to a more valid selection method

27. Utility Analysis (more)
Complete utility analysis evaluates both the benefits and the costs (in money terms) of changing a selection procedure
Mathematical formula (we’ll leave the formula for HR majors & minors when they take MGMT 441: Staffing)
Partial utility analysis uses the Taylor-Russell Table
Table tells us what percentage of our hires will turn out to have acceptable job performance
Doesn’t use money as the unit of measurement
Doesn’t directly consider the costs

28. Taylor-Russell Table
Table tells us what percentage of our hires will turn out to have acceptable job performance
If the table gives an answer of “.67” in a particular situation, it means that 67% of the people hired in the situation will turn out to have acceptable job performance
Which implies that 100% − 67% = 33% of the people we hire in the situation will turn out to have unacceptable job performance
67% good hires (true positives)
33% poor hires (false positives)

29. Taylor-Russell Table To use the table, we need to estimate 3 things:
Base rate of success (BRS): What percentage of our applicant pool could do the job well?
Estimate how good a job of recruiting we’ve done: Do we have a good pool of applicants, or a bad pool, or something in between?
If everyone in the pool could do the job well (BRS = 100%), then we could randomly hire anyone in the pool
Level of validity (r): What’s the validity coefficient for our selection method?
Selection ratio (SR): What percentage of the applicant pool are we going to hire?

30. Taylor-Russell Table
BRS: determines top, middle, or bottom part of table
r: determines which row
SR: determines which column
Source of table: Fisher, Schoenfeldt, & Shaw (2006), Table 7.2, p. 307

31. Taylor-Russell Table Example 1: Example 2: Example 3: Example 4:
BRS = 50%
r = 0.25
SR = 10%
Answer = 67%
Example 2:
SR = 5%
Answer = 70%
Example 3:
r = 0.50
Answer = 84%
Example 4:
Answer = 88%

32. Decision-Making in Selection
Most organizations use more than one selection method to make the selection decision
How do you combine information about an applicant from multiple selection methods to make the selection decision?
Example: An organization uses 3 selection methods to hire a computer programmer:
Résumé evaluation: résumés are rated on a 100-point scale
Programming skills test: test scores go up to 100%
Interview: interviews are rated by interviewers on a 100-point scale

33. Decision-Making in Selection
Additive (compensatory) model
All applicants go through all selection methods
Add together the scores on the selection methods to get a total score for each applicant
Example: Total = résumé score + test score + interview score
Establish a selection cut-off score for the total score
Hire the applicant if the applicant’s total score exceeds the cut-off
Note that a high score on one selection method can compensate for a low score on another selection method

34. Decision-Making in Selection
Multiple cut-off method
All applicants go through all selection methods
Establish a selection cut-off score for each selection method
Hire the applicant if their score on every selection method exceeds the corresponding cut-off score
Example: pass the résumé evaluation and pass the test and pass the interview
Wasteful?
If an applicant fails the résumé evaluation, why waste time and money on the test and the interview?

35. Decision-Making in Selection
Multiple hurdle method
Put the selection methods into a sequence
Each selection method is a “hurdle”
Establish a selection cut-off score for each hurdle
Only applicants who pass the first hurdle go on to the second hurdle
Only applicants who then pass the second hurdle go on to the third hurdle
Only applicants who then pass the third hurdle ..., etc.
Use cost to determine the sequence
Put the cheapest hurdle first, etc.

36. Outline Selection in HR Selection Process Review of Correlation
Criteria for Selection Methods
Using Selection Methods
Utility Analysis
Taylor-Russell Table
Decision-Making in Selection