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“… the development of a valid test requires multiple procedures, which are employed at different stages of test construction … The validation process begins with the formulation of detailed trait or construct definitions … Test items are then prepared to fit the construct definitions. Empirical item analyses follow … Other appropriate internal analyses may then be carried out … The final stage includes validation and cross-validation of various scores and interpretive combinations of scores through statistical analyses against external, real-life criteria.” (Anastasi, 1986, p.3)
Almost any information gathered in the process of developing or using a test is relevant to its validity … If we think of test validity in terms of understanding what a particular test measures, it should be apparent that virtually any empirical data obtained with the test represent a potential source of validity information.” (Anastasi, 1986, p.3)
Test Validity
Test Validation ProcessDefine Objectives
State Inferences
Decide on Methods to Test
Inferences
Collect Evidence
Types of Validity
Content Validity [the extent to which test items represent a domain]
a) Subject Matter Expert Opinions (e.g., CVR statistic)
b) Internal consistency reliability
c) Correlation with other similar tests
Content relevance Domain specification
Content coverage Domain representativeness
1) Perform a job analysis• Description of job tasks• Rating of job tasks on various criteria• Specification of KSAs• Rating of KSAs on various criteria• Link/connect tasks to KSAs
From SIOP Principles: “The characterization of the work domain should be based on accurate and thorough information about the work including analysis of work behaviors and activities, responsibilities of the job incumbents, and/or the KSAOs prerequisite to effective to effective performance on the job. The researcher should indicate what important work behaviors , activities, and worker KSAOs are included in the domain, describe how the content of the domain is linked to the selection procedure, and explain why certain parts of the domain were or were not included in the selection procedure.” (p. 22)
2) Selection of SMEsFrom SIOP Principles: “ The success of the content-based study is closely related to
the qualifications of the subject matter experts (SMEs) … The experts should have thorough knowledge of the work behaviors and activities, responsibilities of job incumbents, and the KSAOs prerequisite to effective to effective performance on the job” (p. 22)
3) Writing (or selecting) and evaluation of selection measure content (test items)
Steps in a Content Validation Effort
TASK -- KSA MATRIX
To what extent is each KSA needed when performing each job task?
5 = Extremely necessary, the job task cannot be performed without the KSA4 = Very necessary, the KSA is very helpful when performing the job task3 = Moderately necessary, the KSA is moderately helpful when performing the job task2 = Slightly necessary, the KSA is slightly helpful when performing the job task1 = Not necessary, the KSA is not used when performing the job task
KSA A B C D E F G H I J K L M N O P Q R
Job Tasks
1
2
3
4
5
6
7
8
9
10
11
12
13
item # KSA B KSA B C item # KSA B KSA B C
1 41
2 42
3 43
4 44
5 45
6 46
7 47
8 48
9 49
10 50
11 51
12 52
Content Validity Issues• Are the job activities and requirements stable across time?
• Does successful performance on the test require the same KSAs as successful performance on the job?
• Is the type (or mode) of testing procedure the same as that required on the job?
• Do some KSAs not required on the job exist on the test?
• Not useful when abstract constructs are being measured (a small inferential leap is required between the test content and job requirements)From Anastasi (1986): “When tests are designed for use within special contexts, the relevant constructs are usually derived from content analysis of particular behavior domains” (p. 7).
From SIOP Principles: “ When selection procedure content is linked to job content, content-oriented strategies are useful. When selection procedure content is less clearly linked to job content, other sources of validity evidence take precedence” (p. 23).
Predictive
[Correlation between test scores of applicants and their performance scores when some time interval has passed after they are hired]
• Range restriction issue on performance scores
• Time, cost, & pragmatic concerns
Criterion-related Validity
Concurrent [Correlation between test scores and performance scores of current employees]• Motivation level• Guessing, Faking• Job experience factor• Range restriction issue on performance scores
Types of Validity (cont.)
Criterion-related Validity Issues
A) Job Stability
B) Reliable and relevant measure of job performanceFrom SIOP Principles: “A relevant, reliable, and uncontaminated criterion(s) must be
obtained or developed. Of these characteristics, the most important is relevance. A relevant criterion is one that reflects the relative standing of employees with respect to important work behavior(s) or outcome measure(s). If such a criterion measure does not exist or cannot be developed, use of a criterion-related validation strategy is not feasible (p. 14).
C) Use of a representative sample of people and jobs
D) Large sample (on predictor and criterion)From SIOP Principles: “A competent criterion-related validity study should be
based on a sample that is reasonably representative of the work and candidate pool … A number of factors related to statistical power can influence the feasibility of a criterion-related study. Among these factors are the degree (and type) of range restriction in the predictor or the criterion, reliability of the criterion, and statistical power (p. 14)
Legal Issues and Criterion-related Validity
• Court focus on the content of measures as opposed to criterion validity evidence (relationship between test cores and job performance)
• Emphasis on the legal history of tests
• Criterion-validity emphasis versus concurrent validity designs
• Statistical significant relationships are not always acceptable (consideration of other factors such as test utility)
• Reliability of both the criterion (job performance) and the predictor (test)
• Restriction of range (on both the test and job performance measure)
• Contamination of the criterion (e.g., measure of job performance is affected by other variables rather than one’s ability or knowledge)
Factors Affecting the Validity Coefficient[correlation between a test and job
performance]
Standard error of estimate
(validity coefficient):y’ = y 1 - r
2xy
y = standard deviation of y
(criterion)
r2
xy = correlation between x
and y squared
Correction for Attenuation
Observed validity coefficientT =
x y xy0
yyCriterion reliability
Validity coefficient
= =
S
S1
1
of unrestricted sample
of restricted sample
1 - + 2 2S 2
1
S 21
Range of Restriction (Predictor)
1 - (1 - )2S
S
2121
Range Restriction (Criterion)
Selection Ratio (SR) = n
N
# Job openings
# Applicants
Test Validity [Criterion-related]: The extent to which test scores correlate with job performance scores [Range is from 0 to 1.0]
Test Utility Key Points
Proportion of “Successes” Expected Through the Use of Test of Given Validity and Given Selection Ratio, for Base Rate .60.
(From Taylor & Russell, 1939, p. 576)
Selection RatioValidity .05 .10 .20 .30 .40 .50 .60 .70 .80 .90 .95 .00 .60 .60 .60 .60 .60 .60 .60 .60 .60 .60 .60 .05 .64 .63 .63 .62 .62 .62 .61 .61 .61 .60 .60 .10 .68 .67 .65 .64 .64 .63 .63 .62 .61 .61 .60 .15 .71 .70 .68 .67 .66 .65 .64 .63 .62 .61 .60 .20 .75 .73 .71 .69 .67 .66 .65 .64 .63 .62 .61
.25 .78 .76 .73 .71 .69 .68 .66 .65 .63 .62 .61 .30 .82 .79 .76 .73 .71 .69 .68 .66 .64 .62 .61 .35 .85 .82 .78 .75 .73 .71 .69 .67 .65 .63 .62 .40 .88 .85 .81 .78 .75 .73 .70 .68 .66 .63 .62 .45 .90 .87 .83 .80 .77 .74 .72 .69 .66 .64 .62 .50 .93 .90 .86 .82 .79 .76 .73 .70 .67 .64 .62 .55 .95 .92 .88 .84 .81 .78 .75 .71 .68 .64 .62 .60 .96 .94 .90 .87 .83 .80 .76 .73 .69 .65 .63 .65 .98 .96 .92 .89 .85 .82 .78 .74 .70 .65 .63 .70 .99 .97 .94 .91 .87 .84 .80 .75 .71 .66 .63 .75 .99 .99 .96 .93 .90 .86 .81 .77 .71 .66 .63 .80 1.00 .99 .98 .95 .92 .88 .83 .78 .72 .66 .63 .85 1.00 1.00 .99 .97 .95 .91 .86 .80 .73 .66 .63 .90 1.00 1.00 1.00 .99 .97 .94 .88 .82 .74 .67 .63 .95 1.00 1.00 1.00 1.00 .99 .97 .92 .84 .75 .67 .631.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 .86 .75 .67 .63
Note: A full set of tables can be found I Taylor and Russell (1939) and in McCormick and Ilgen (1980, Appendix B).
Mean Standard Criterion Score of Accepted Cases in Relation to Test Validity and Selection Ratio(From Brown & Ghiselli, 1953, p. 342)
Validity CoefficientSelectionRatio .00 .05 .10 .15 .20 .25 .30 .35 .40 .45 .50 .55 .60 .65 .70 .75 .80 .85 .90 .95 1.00
.05 .00 .10 .21 .31 .42 .52 .62 .73 .83 .94 1.04 1.14 1.25 1.35 1.46 1.56 1.66 1.77 1.87 1.98 2.08
.10 .00 .09 .18 .26 .35 .44 .53 .62 .70 .79 .88 .97 1.05 1.14 1.23 1.32 1.41 1.49 1.58 1.67 1.76 .15 .00 .08 .15 .23 .31 .39 .46 .54 .62 .70 .77 .85 .93 1.01 1.08 1.16 1.24 1.32 1.39 1.47 1.55 .20 .00 .07 .14 .21 .28 .35 .42 .49 .56 .63 .70 .77 .84 .91 .98 1.05 1.12 1.19 1.26 1.33 1.40.25 .00 .06 .13 .19 .25 .32 .38 .44 .51 .57 .63 .70 .76 .82 .89 .95 1.01 1.08 1.14 1.20 1.27.30 .00 .06 .12 .17 .23 .29 .35 .40 .46 .52 .58 .64 .69 .75 .81 .87 .92 .98 1.04 1.10 1.16 .35 .00 .05 .11 .16 .21 .26 .32 .37 .42 .48 .53 .58 .63 .69 .74 .79 .84 .90 .95 1.00 1.06.40 .00 .05 .10 .15 .19 .24 .29 .34 .39 .44 .48 .53 .58 .63 .68 .73 .77 .82 .87 .92 .97.45 .00 .04 .09 .13 .18 .22 .26 .31 .35 .40 .44 .48 .53 .57 .62 .66 .70 .75 .79 .84 .88.50 .00 .04 .08 .12 .16 .20 .24 .28 .32 .36 .40 .44 .48 .52 .56 .60 .64 .68 .72 .76 .80.50 .00 .04 .07 .11 .14 .18 .22 .25 .29 .32 .36 .40 .43 .47 .50 .54 .58 .61 .65 .68 .72.60 .00 .03 .06 .10 .13 .16 .19 .23 .26 .29 .32 .35 .39 .42 .45 .48 .52 .55 .58 .61 .64.65 .00 .03 .06 .09 .11 .14 .17 .20 .23 .26 .28 .31 .34 .37 .40 .43 .46 .48 .51 .54 .57.70 .00 .02 .05 .07 .10 .12 .15 .17 .20 .22 .25 .27 .30 .32 .35 .37 .40 .42 .45 .47 .50.75 .00 .02 .04 .06 .08 .11 .13 .15 .17 .19 .21 .23 .25 .27 .30 .32 .33 .36 .38 .40 .42.80 .00 .02 .04 .05 .07 .09 .11 .12 .14 .16 .18 .19 .21 .22 .25 .26 .28 .30 .32 .33 .35.85 .00 .01 .03 .04 .05 .07 .08 .10 .11 .12 .14 .15 .16 .18 .19 .20 .22 .23 .25 .26 .27.90 .00 .01 .02 .03 .04 .05 .06 .07 .08 .09 .10 .11 .12 .13 .14 .15 .16 .17 .18 .19 .20.95 .00 .01 .01 .02 .02 .03 .03 .04 .04 .05 .05 .06 .07 .07 .08 .08 .09 .09 .10 .10 .11
Selection Ratio Example (cont.)
Ns rxy SDyZx – NT (C)
# of applicants selected
validity coefficient
standard deviation of job performance in
dollar terms
average score on the selection procedure of those selected (standard score)
number of applicants assessed
cost of assessing each applicant
Example of Brogden and Cronbach & Gleser Models
Construct ValidityMultitrait-Multimethod Matrix (Campbell & Fiske, 1959)
Types of Validity (cont.)
Construct Validity [extent to which a test assesses the construct it intends
to measure] • Correlation between scores measuring a construct (e.g., anxiety) with one method (e.g., paper & pencil) with scores on the same construct using a different method (e.g., interview) [Convergent validation]• Correlation between scores measuring a construct (e.g., anxiety) using one method (e.g., paper & pencil) with scores on a different construct (e.g., leadership) assessed with a different method (e.g., interview) [Discriminant validation]
“Construct validation is indeed a never-ending process. However, that should not preclude using the test operationally to help solve practical problems and reach real-life decisions as soon as the available validity information has reached an acceptable level for a particular application. This level varies with the type of test and the way it will be used. Establishing this level requires informed professional judgment within the appropriate specialty of professional practice.” (Anastasi, p.4)
Non minority
Minority
Performance Criterion
Satisfactory
Unsatisfactory
Reject AcceptPredictor Score
Equal validity, unequal criterion means
- Equal test scores; Minorities performing less well on job (over predicting performance)
- Minorities hired same as non minorities but probability of success is small. Can reinforce existing stereotypes.
Minority
Non minority
Satisfactory
Unsatisfactory
PerformanceCriterion
Reject AcceptPredictor Score
Equal validity, unequal predictor means
- Job performance is equal
- Test scores are greater for non-minorities
Intercept Bias (Test)
Minority
Non minority
Accept Reject
Performance Criterion
Unsatisfactory
Satisfactory
Equal predictor means, but validity only for non minority groups
Predictor score
• Equal test scores and criterion scores• No validity for minorities (only should be used for non minorities)• No adverse impact same numbers hired in each group- However, more non-minorities will succeed on jobs; can reinforced stereotypes
•
Situational specificity or
Generalizibility of test validity across samples?
Fluctuations in validity coefficients may often be due to:
• Small sample sizes (e.g., many have samples of 50 or less employees)
• Unreliable criterion measures
• Restriction of range in employee samples
Some evidence that certain tests (e.g., aptitude tests) may can be generalized across a variety of occupations
Significant effect foundNo significant effect found
Findings of study
No significanc
e exists
Significance exists
Reality
Correct decision(accept null)
Correct decision(reject null)
Type I error (“false positive”)
Type II error (“false positive”)
“Every experiment may be said to exist only in order to give the facts a chance of disproving the null hypothesis.” (Fisher, 1935, p.19)
Statistical Power and Hypothesis Testing