Transcript PSY 6430 Unit 5 - Alyce Dickinson

PSY 6430 UNIT 5
Validity
Determining whether the selection instruments
are job-related
Today and Wednesday: Lecture
Exam: Monday, 3/18
1
SO1: NFE, Validity, a little review
2



Predictor = test/selection instrument
Use the score from the test to predict who will
perform well on the job
Possible confusion (again)
 You
need to determine the validity of the test based on
your current employees
 Then you administer it to applicants and select
employees based on the score
(a few students had a problem distinguishing between validity and reliability on E4, example next)
SO1: NFE, Validity, example
3






Administer a test to current employees
Obtain measures of how well they perform on the job
Correlate the test scores with the performance measures
Assume: The correlation is statistically significant
Assume: Current employees who score 50-75 also are
performing very well on the job
Now you administer the exam to applicants, predicting that
those who score 50-75 will also perform well on the job
(main point next slide)
SO1: NFE, Validity main point
4



You determine the validity of a selection test or
instrument based on your current employees
Then after establishing the validity or job
relatedness of the test
Give the test to applicants and select them on
the basis of their test scores
SO2: Reliability vs. Validity
5


Reliability
Is the score on the measure stable and
dependable?
Are you actually measuring what you want to be
measuring?
Validity
Is the measure related to performance on the
job?
SO3: Relationship between reliability and validity
6




A measure can be reliable, but not valid
However, a measure cannot be valid unless it is
reliable
*Reliability is a necessary but not sufficient
condition for validity
Text gives a perfect example
You can reliably measure eye color, however, it
may not be related to job performance at all
*key point
Types of validation procedures
7






Content: expert judgment
Criterion-related: statistical analyses (concurrent & predictive)
Construct (but not practical-not covering this)
Validity generalization (transportable, no local validity study –
jobs are similar)
Job component validity (not covering this in this unit, but will
return to it briefly in the next unit, transportable, job
elements/components are similar but jobs are not)
Small businesses: Synthetic validity (not covering it, not very
relevant now –content validity)
(main types are the two kinds of criterion-related and content validity; construct really a hold over from test construction - not very
relevant - I have only seen this used by a few organizations – create their own tests; touch on validity generalization, but right now
while validity generalization has excellent professional support, may not be legal - professional guidelines depart from legal; in one
case, 6th Circuit Court ruled it illegal as a matter of law based on Griggs/Duke and Albermarle - 1987)
SO5 NFE but 7B is: Difference between
content and criterion-related validity
8

Criterion-related validity is also called
“empirical” validity
 Concurrent
validity
 Predictive validity

This type of validity relies on statistical analyses
(correlation of test scores with measures of job
performance)
 Measures
(content next slide)
of job performance = criterion scores
SO5 NFE but related to 7B which is: Difference
between content and criterion-related validity
9


Content validity, in contrast, relies on expert
judgment and a match between the “content” of
the job and the “content” of the test
Expert judgment refers to
 the
determination of the tasks and KSAs required
to perform the job via a very detailed type of job
analysis
 linking the KSAs to selection procedures that
measure them
NFE: Intro to content validity
10

You do NOT use statistical correlation to validate
your tests
 Validation
is based “only” on your job analysis
procedures and matrix between KSAs and selection
measures

It is much more widely used than criterion-related
validity
 Particularly
since Supreme Court ruled it was OK to
use for adverse impact cases (1995)
SO6: Two reasons why content
validity is often used
11

It can be used with relatively small number of
employees
 Large
sample sizes are required to use criterionrelated validity due to the correlation procedures
 The text later when talking about criterion-related
validity indicates you may need over several
hundred
 Dickinson: usually 50-100 is adequate
 How many companies have that many current
employees in one position?
(small number of incumbents and applicants)
SO6: Two reasons why content
validity is often used
12

Many organizations do not have good job
performance measures

You need good performance criterion measures to
do a criterion-related validity study because you
correlate the test scores with job performance
measures
SO7A: Content vs. criterion-related validity and
the type of selection procedure
13


If you use content validity you should write the
test, not select an off-the-shelf test
If you use criterion-related validity, you can do
either
 It
is much easier and less time consuming to use an
off-the-shelf test than to write one!
(VERY IMPORTANT!; book waffles on this a bit, indicating that emphasis should be placed on constructing a test,
But only in rare situations would I recommend selecting off-the-shelf test with content validity - legally too risky; why, next slide)
SO7A: Why should you write the test if you use
content validity? (this slide, NFE)
14


Content validity relies solely on the job analysis
The KSAs must be represented proportionately on the
selection test as indicated in the job analysis in terms of:





Their relative importance to the job
The percentage of time they are used by the employees
It is highly unlikely that an off-the-shelf test will proportionately
represent the KSAs as determined by your job analysis
In some discrimination court cases, the judge has gone
through the test item by item to determine whether the items
were truly proportional to the KSAs as determined by the
job analysis
Both professional measurement reason and legal reason to
write the test rather than using an off-the-shelf test
SO7B: Content vs. criterion-related validity: Differences
in the basic method used to determine validity (review)
15

Content validity
 Relies
solely on expert judgment - no statistical
verification of job-relatedness

Criterion-related validity
 Relies
on statistical prediction to determine jobrelatedness
(I am not going to talk about SO8, face validity; very straightforward)
SO9: What is the “heart” of any validation study
and why?
16


Job analysis
The job analysis determines the content domain of
the job – the tasks and KSAs that are required to
perform the job successfully
SO10: Major steps of content validity - very,
very specific requirements for the job analysis
17



Describe tasks for the job
*Determine the criticality and/or importance of
each of the tasks
Specify the KSAs required for EACH task
 KSAs
must be linked to each task (NFE)
*Now because of ADA, is it an essential function?
(cont. next slide)
SO10: Major steps of content validity, cont.
18

Determine the criticality and/or importance of each KSA*


Operationally define each KSA
Describe the relationship between each KSA and each task statement


You can have KSAs that are required for only one or two tasks, or you can have KSAs
that are required to perform several tasks
The more tasks that require the KSAs, the more important/critical they are
Describe the complexity or difficulty of obtaining each KSA (formal
degree, experience)
 Specify whether the employee must possess each KSA upon entry or
whether it can be acquired on the job (cannot test for a KSA if it can
be learned within 6 months)
 Indicate whether each KSA is necessary for successful performance of
the job
*Only the first major point will be required for the exam, but I want to
stress how detailed your job analysis must be for content validity

(cont on next slide)
SO10: Major steps of content validity, cont.
19

Link important job tasks to important KSAs* (FE)





Reverse analysis; you have linked the KSAs to the tasks, now you must
link the KSAs to the tasks (NFE)
KSA # 1 may be relevant to Tasks 1, 6, 7, 10, 12, & 22
KSA # 2 may be relevant to Tasks 2, 4, & 5
Etc.
(NFE) Develop test matrix for the KSAs

If you want see how you go from the task analysis to the actual test,
turn ahead to Figures 7.12, 7.13, 7.14, 7.15, and 7.16 on pages
283-286 and Figure 7.17 on page 290
SO11: When you can’t use content validity
according to the Uniform Guidelines
20

When assessing mental processes, psychological constructs,
or personality traits that cannot be directly observed, but
are only inferred




You cannot use content validity to justify a test for judgment,
integrity, dependability, extroversion, flexibility, motivation,
conscientiousness, adaptability
The reason for that is that you are basing your job analysis on
expert judgment - and judgment is only going to be reliable if you
are dealing with concrete KSAs such as mechanical ability, arithmetic
ability or reading blue prints
The more abstract the KSA, the less reliable judgment becomes
If you can’t see it, if you can’t observe it, then the leap from the task
statements to the KSAs can result in a lot of error
(text mentions three; I am having you learn the first one and one I added in the SOs -- these are the two that
are most violated in practice; the second one is relevant to BOTH content and criterion-related so shouldn’t be listed
under when you can’t use content validity: cannot test for KSAs that can be learned on the job)
SO11: When you can’t use content validity
according to the Uniform Guidelines, cont.
21

When selection is done by ranking test scores or banding
them (from U1)



If you rank order candidates based on their test scores and select on
that basis, you cannot use content validity - you must use criterionrelated validity
If you band scores together, so those who get a score in a specified
range of scores are all considered equally qualified, you cannot use
content validity - you must use criterion-related validity
Why? If you use ranking or banding, you must be able to prove that
individuals who score higher on the test will perform better on the job
- the only way to do that is through the use of statistics
The only appropriate (and legally acceptable) cut-off score
procedure to use is a pass/fail system where everyone
above the cut-off score is considered equally qualified
(only relevant if adverse impact
)
Criterion-related validity studies:
Concurrent vs. predictive
22


SO13A: Concurrent validity
Administer the predictor to current employees and correlate
scores with measures of job performance
Concurrent in the sense that you have collected both
measures at the same time for current employees
SO18A: Predictive validity
Administer the predictor to applicants, hire the applicants,
and then correlate scores with measures of job
performance collected 6-12 months later
Predictive in the sense that you do not have measures of job
performance when you administer the test - you collect them
later
(comparison of the two, SO13A, describe concurrent validity; SO18A, describe predictive validity)
Predictive Validity: Three basic ways to do it
23



Pure predictive validity: by far the best
Administer the test to applicants and randomly
hire
Current system: next best, more practical
Administer the test to applicants, use the current
selection system to hire (NOT the test)
Use test to hire: bad, bad, bad both
professionally and legally
Administer the test, and use the test scores to hire
applicants
(going to come back to these and explain the evaluations; text lists the third as an approach! Click: NO!!)
SO13B: Steps for conducting a
concurrent validity study
24

Job analysis: Absolutely a legal requirement

Discrepancy between law and profession (learn for exam)




Law requires a job analysis (if adverse impact & challenged)
Profession does not as long as the test scores correlate significantly with
measures of job performance
Determine KSAs and other relevant requirements from the job
analysis, including essential functions for purposes of ADA
Select or write test based on KSAs (learn for exam)


May select an off-the-shelf test or
Write/construct one
SO13B: Steps for conducting a
concurrent validity study
25

Select or develop measures for job performance





Sometimes a BIG impediment because organizations often do not
have good measures of performance
Administer test to current employees and collect job
performance measures for them
Correlate the test scores with the job performance measures
(SO14: add this step) Determine whether the correlation is
statistically significant at the .05 level
(not necessary for exam) Administer test to job applicants
and select on the basis of the test scores
SO15: The basic reason that accounts for all of
the weaknesses with concurrent validity
26




All of the weaknesses have to do with differences between
your current employees and applicants for the job
You are conducting your study with one sample of the
population (your employees) and assuming conceptually
that your applicants are from the same population
However, your applicants may not be from the same
population - they may differ in important ways from your
current employees
Ways that would cause them (as a group) to score
differently on the test or perform differently on the job,
affecting the correlation (job relatedness) of the test
(text lists several weaknesses and all of them really relate to one issue; dealing with inferential statistics here)
SO16: Restriction in range
27


With criterion-related validity studies the ultimate proof
that your selection test is job related is that the correlation
between the test scores and job performance measures is
statistically significant
A high positive correlation tells you




People who score well on the test also perform well
People who score middling on the test also are middling performers
People who score poorly on the test also perform poorly on the job
In order to obtain a strong correlation you need


People who score high, medium, and low on the test
People who score high, medium, and low on the performance
measure
(before really understanding the weaknesses related to concurrent validity and why pure predictive validity is the most sound
type of validation procedure, you need to understand what “restriction in range” is and how it affects correlation coefficient; related
to some of the material from the last unit on reliability - so if you understood it in that context, this is the same conceptual issue)
SO16: Restriction in range, cont.
28

That is, you need a range of scores on BOTH the test and the
criterion measure in order to get a strong correlation



If you only have individuals who score about the same on the exam,
regardless of whether some perform well, middling, and poorly, you
will get a zero correlation
Similarly if you have individuals who score high, medium, and low on
the test, but they all perform reasonably the same, you will get a zero
correlation
Any procedure/factor that decreases the range of scores on
either the test or the performance measure



Reduces the correlation between the two and, hence,
Underestimates the true relationship between the test and job
performance
That is, you may conclude that your test is NOT valid, when in fact, it
may be
SO16: Restriction in range, cont.
29


Restriction in range is the technical term for the
decrease in the range of scores on either or both
the test and criterion
Concurrent validity tends to restrict the range of
scores on BOTH the test and criterion, hence
underestimating the true validity of a test
(cont on next slide)
SO16: Restriction in range, cont.
30

Why? You are using current employees in your sample




Your current employees have not been fired because of poor
performance
Your current employees have not voluntarily left the company
because of poor performance
Your current employees have been doing the job for a while and
thus are more experienced
All of the above would be expected to



Result in higher test scores than for the population of applicants
Result in higher performance scores than for the population
Thus, restricting the range of scores on both the test and the
performance criterion measure
(diagrams on next slide)
SO16: Restriction in range, cont.
31
Top diagram
 No
restriction in range
 Strong correlation
High
Performance

Low
Low
High
Test Scores
Bottom diagram
 Restriction
in range
 Test
scores and
 Performance scores
 Zero
correlation
High
Performance

Low
Low
High
Test Scores
(extreme example, but demonstrates point - concurrent validity is likely to restrict range on both, underestimating true validity)
SO17A&B: Factors that affect
concurrent validity
32

A. Why the length of employment of current
employees may affect the results of a concurrent
validity study

An aging, experienced work force has been performing
the job for a long time, thus




You would expect them to score better on an ability test than
inexperienced job applicants AND
You would expect them all to perform reasonably well on the
job
Thus, you have restricted the range on both your test and
performance scores, which would result in a lower correlation
coefficient than would occur with applicants
Underestimate the job-relatedness of the test
(17a&b are really questions about restriction in range)
SO17A&B: Factors that affect
concurrent validity
33

Why rejected applicants, turnover and promotions would
affect the results of a concurrent validity study

Rejected applicants and those that leave are likely to be poorer
performers; your most skilled workers are promoted: what is left
are employees who perform similarly on the test & performance
measure
 You would expect the remaining, current employees to score
more similarly on an ability test than job applicants AND
 You would expect them to perform similarly on the job
 Thus, you have restricted the range on both your test and
performance scores, which would result in a lower correlation
coefficient than would occur with applicants
 Underestimate the job-relatedness of the test
(b same logic as A; both have to do with restriction in range)
SO18: Predictive validity
34

SO18A: Predictive validity (review)
Administer the predictor to applicants, hire the applicants,
and then correlate scores with measures of job
performance collected 6-12 months later
Predictive in the sense that you do not have measures of job
performance when you administer the test - you collect them
later, hence, you can determine how well your test actually
predicts future performance
SO18B: Steps for a predictive validity study
35



Job analysis: Absolutely a legal requirement
Determine KSAs and other relevant requirements
from the job analysis, including the essential
functions for purposes of ADA
Select or write test based on KSAs*
 You
may select an off-the-shelf test or
 Write/construct one

Select or develop measures for job performance
*Learn this point for the exam
(first four steps are exactly the same as for a concurrent validity study)
SO18B: Steps for a predictive validity study
36

Administer the test to job applicants and file the
results away
 Do
NOT use the test scores to hire applicants (I’ll
come back to this later)




After a suitable time period, 6-12 months, collect
job performance measures (or training measures)
Correlate the test scores with the performance
measures
(SO18B: add this step) Determine whether the
correlation is statistically significant
(NFE) If so, administer test to new job applicants
and select on the basis of the scores
SO19: Two practical (not professional)
weaknesses of predictive validity
37

Time it takes to validate the test
Need appropriate time interval after applicants are hired
before collecting job performance measures
 If the organization only hires a few applicants per month, it
may take months or even a year to obtain a large enough
sample to conduct a predictive validity study (N=50-100)

SO19: Two practical (not professional)
weaknesses of predictive validity
38

Very, very difficult to get managers to ignore the test
data (politically very difficult)
Next to impossible to get an organization to randomly hire some poor employees ARE going to be hired
 Also difficult to convince them to hire without using the test
score (but much easier than getting them to randomly hire)

(I don’t blame them; admissions process for I/O program)
SO20A: Best predictive validity design
39


Figure 5.5 lists 5 types of predictive validity designs
Follow-up: Random selection (pure predictive validity)
Best design
 No problems whatsoever from a measurement perspective;
completely uncontaminated from a professional perspective


Follow-up: Use present system to select
OK and more practical, but
 It will underestimate validity if your current selection system is
valid; and the more valid it is the more it will underestimate
the validity of your test
 Why?

(answer not on slide)
SO20C: Predictive validity, selection by scores
40

Select by test score: Do NOT do this!!!

Professional reason:
 If your selection procedure is job related, it will greatly
underestimate your validity - and, the more job related
the selection procedure is, the greater it will
underestimate validity.
 In fact, you are likely to conclude that your test is not
valid when in fact it is
 Why? You are severely restricting the range on both your
test and your job performance measures!
(professional and legal reasons not to do this)
SO20C: Predictive validity, selection by scores
41
 Legal
 If
reason:
adverse impact occurs you open yourself up to an
unfair discrimination law suit
 You have adverse impact, but you do not know whether
the test is job related
SO20: NFE, Further explanation of types of
predictive validity studies
42

Hire, then test and later correlate test scores and job
performance measures
If you randomly hire, this is no different than pure predictive
validity: #1 previously, Follow-up: Random selection
 If you hire based on current selection system, this is no
different than #2 previously, Follow-up: Select based on
current system

(one more slide on this)
SO20: NFE, Further explanation of types of
predictive validity studies
43

Personnel file research - applicants are hired and their
personnel records contain test scores or other
information that could be used as a predictor. At a
later date, job performance scores are obtained.

This is no different than Follow-up: Select based on current
system
For exam: Rank order of criterion-related validity
studies in terms of professional measurement standards
44
1.
2.5
2.5
4.
Predictive validity (pure) - randomly hire
Predictive validity - current selection system
Concurrent validity
Predictive validity - test scores to hire
Which is better: Predictive vs. concurrent,
research results (NFE)
45

Data that exist suggest that:
 Concurrent
validity is just as good as predictive validity
for ability tests (most data)
 May not be true for other types of tests such as
personality and integrity tests
 Studies
have shown differences between the two for these
type of tests - so proceed with caution!
SO21: Sample size needed for a criterionrelated validity study (review)
46

Large samples are necessary
 The
text indicates that frequently over several hundred
employees are often necessary
 Dickinson maintains that a sample of 50-100 is usually
adequate - learn Dickinson’s number

What do companies do if they do not have that
many employees?
 They
use content validity
 They could possibly also use validity generalization or
job component validation, but I want to hold off on that
for a moment – these are legally risky
SO23: NFE, Construct validity
47



Every selection textbook covers construct validity
I am not covering it for reasons indicated in the
SOs, but will talk about it at the end of class if I
have time
Basic reason for not covering it is that while
construct validity is highly relevant for test
construction, very, very few organizations use this
approach - it’s too time consuming and expensive


First, the organization develops a test and determines whether it is
really measuring what it is supposed to be measuring
Then, they determine whether the test is job related
SO27: Validity generalization, what it is
48


Validity generalization is considered to be a form of
criterion-related validity, but you don’t have to conduct the
validity study in your organization for your employees
Rather you take validity data from other organizations for
the same or very similar positions and use those data to
justify the use of the selection test(s)

Common jobs: computer programmers and systems analysts, set-up
mechanics, clerk typists, sales representative, etc.
(I am skipping to SO27 for the moment, SOs24-26 relate to statistical concepts about correlation; organization of this chapter
Is just awkward. I want to present all of the validity procedures together, and then compare them with respect to when you
should/can use one or the other. Then, I’ll return to SOs 24-26: cont on next slide)
SO27: Validity generalization, what it is
49


Assumption is that those data will generalize to your position
and organization
Thus, you can use this approach if you have a very small
number of employees and/or applicants*
*Note this point well
SO28: Validity generalization, cont.
50

Testing experts completely accept the legitimacy of validity
generalization




Primarily based on the stellar work of Schmidt and Hunter (who was
a professor at MSU until he retired)
Gatewood, Field, & Barrick believe this has a bright future
Frank Landy (also a legend in traditional I/O) is much more
pessimistic about it
Wording of the CRA of 1991 may have made this illegal


There has not been a test case
No one wants to be the test case (you should not be the test case)
(this slide, NFE, cont. on nxt slide)
SO28: Validity generalization, cont.
51

Actually have come full circle with respect to validity
generalization and its acceptance by testing specialists

In the early days of testing, validity generalization was accepted



If a test was valid for a particular job in one organization it would be
valid for the same or a similar position in another organization
It then fell into disfavor, with testing specialists reversing their
position, and adhering to situational specificity
Now, based on Schmidt and Hunter’s work, it is again embraced by
testing specialists
(this slide, also NFE)
SO29 FE: Two reasons why CRA 1991
may make validity generalization illegal
52
Both reasons relate to the wording in the CRA that the only
acceptable criterion measure (job performance measure) is
actual job performance

1.
2.
Criterion-related validity studies have often included the use of
personnel data such as absenteeism, turnover, accident rates, training
data, etc. as the criterion or in multiple regression/correlation studies as
one or more of the criteria – this may not be considered job
performance under CRA 1991
If courts interpret “actual” in actual job performance literally, then the
courts could maintain that only the performance of the workers who
participate in the study would be an acceptable criterion measure
Could ban the use of data from other organizations and require local
validity studies (local meaning in your own organization)
SO30: Correction!!
53


The material in this study objective relates to
synthetic validity (pages 199-201) in the section
“Validation Options for Small Businesses” not job
component validity
I am going to talk about job component validity in
the next unit – because it is tied to a particular type
of job analysis procedure – the Position Analysis
Questionnaire
SO30NFE: Synthetic validity (briefly)
54

This is a way to conduct a criterion-related validity study with
small samples as long as you have related jobs in the
organization




Jobs that require some of the same KSAs
I believe it has become obsolete since the Supreme Court ruled
in 1995 that content validity is an acceptable defense for
adverse impact
Criterion-related studies are simply more costly than content
validity
Selection experts, however, will always prefer criterion-related
studies
SO31: Interesting fact (and for the exam)
55

In a 1993 random survey of 1,000 organizations listed in
Dun’s Business Rankings with 200 or more employees, the
percentage of firms indicating that they had conducted
validation studies of their selection measures was:
24%
In today’s legal environment, the other organizations
could find themselves in a whole world of hurt!
(click, click!)
Factors that affect the type of validity
study: When to use which validity strategy
56

Four main factors that influence the type of
validity study you can do
 Sample
size
 Cut-off score procedures
 Type of attribute measured: observable or not
 Type of test: write or off-the-shelf
(on the exam, I am likely to give you situations and ask you, given the situation, what type of validity strategy could you use and why:
That is, what options do you have? That’s exactly the type of decision you are going to have to make in organizations. So, to make it
easier, and summarize things: Include validity generalization in your answers
Factors that affect the type of validity
study: When to use which validity strategy
57

Sample size
Large # employees
Concurrent
(all forms, OK)
Predictive
Content
Validity generalization
Small # employees
Content
Validity generalization
(it’s OK to use content and validity gen with large sample sizes; many orgs do use content!)
Factors that affect the type of validity
study: When to use which validity strategy
58

Cut-off score procedures
Minimum (pass/fail)
Concurrent
(all forms, OK)
Predictive
Content
Validity generalization
Ranking or banding
(only criterion-relatedall but content)
Concurrent
Predictive
Validity generalization
(validity generalization is based on correlation, even if you don’t do the study yourself, so remember it is considered a type
Of criterion-related study)
Factors that affect the type of validity
study: When to use which validity strategy
59

Attribute being measured
Observable
Concurrent
(all forms, OK)
Predictive
Content
Validity generalization
Not observable
(only criterion-relatedall but content)
Concurrent
Predictive
Validity generalization
(personality, extraversion, social sensitivity, flexibility, integrity, etc.)
Factors that affect the type of validity
study: When to use which validity strategy
60

Type of test
Write/construct
Concurrent
(all forms, OK)
Predictive
Content
Validity generalization
Off-the-shelf
(only criterion-relatedall but content)
Concurrent
Predictive
Validity generalization
(next slide, back to SO 24; interpretation of validity correlation)
SO24: Statistical interpretation of a validity
coefficient
61



Recall, r = correlation coefficient
r2 = coefficient of determination
Coefficient of determination:
The percentage of variance on the criterion that can be explained by
the variance associated with the test

r = .50, to statistically interpret it:



r2 = .25
25% of the variance on job performance can be explained by the
variance on the test
Less technical, but OK
25% of the differences between individuals on the job performance
measure can be accounted for by differences in their test scores
SO25: Validity vs. reliability correlations
62

You interpret a validity correlation coefficient
very differently than a reliability correlation
coefficient
 You
square a validity correlation coefficient
 You do NOT square a reliability correlation
coefficient

Why?
With a reliability correlation coefficient you are basically
correlating a measure with itself
 Test-retest
reliability
 Parallel or alternate form reliability
 Internal consistency reliability (split half)
(I am not going to go into the math on that to prove that to you)
SO25B: Validity vs. reliability correlations,
examples for test
63



You correlate the test scores from a mechanical ability test
with a measure of job performance
The resulting correlation coefficient is .40
How would you statistically interpret that?
16% of the differences in the job performance of
individuals can be accounted for by the differences
in their test scores
SO25B: Validity vs. reliability correlations,
examples for test
64



You administer a computer programming test to a group of
individuals, wait 3 months and administer the same test to
the same group of individuals.
The resulting correlation coefficient is .90
How do you statistically interpret that correlation
coefficient?
90% of the differences in the test scores between
individuals are due to true differences in computer
programming and 10% of the differences are due
to error
Different types of correlation coefficients: or why it is a
good idea to take Huitema’s correlation and regression
65


The most common type of correlation to use is the
Pearson product moment correlation
However, you can only use this type of correlation if
 You
have two continuous variables, e.g., a range of
scores on both x and y
 If the relationship between the two variables is linear
 Some
have shown a curvilinear relationship between
intelligence test scores and performance of sales
representatives
(NFE, I think)
Different types of correlation coefficients: or why it is a
good idea to take Huitema’s correlation and regression
66

Point biserial coefficient is used when one variable is continuous
and the other is dichotomous




High school diploma vs. no high school diploma (X)
Number of minutes it takes a set-up mechanic to set up a manufacturing
line (Y)
x is dichotomous, y is continuous
Phi coefficient is used when both variables are dichotomous



High school diploma or no high school diploma (X)
Pass or fail performance measure (Y)
Both x and y are dichotomous
(NFE, I think, one more slide on this)
Different types of correlation coefficients: or why it is a
good idea to take Huitema’s correlation and regression
67

Rho coefficient - Spearman’s rank order correlation - when you
rank order both x and y, and then correlate the ranks



Rank order in test scores
Rank order number of minutes it takes set-up mechanics to set up a
manufacturing line
Use rank order when either your x or y scores are not normally
distributed - that is, when there are a few outliers - either very high
scores on either or very low scores on either
(NFE, I think,last slide)
END OF UNIT 5
Questions?
Comments?
68
NFE: Back to construct validity
69




Construct validity:
Does the test actually measure the “construct” you think it is
measuring?
This is a hold-over from the more traditional cognitive
psychology and psychometrics field that philosophically
believes in mind-body dualism (mentalism)
That is, there really is something called “general
intelligence” that is more than just the sum of what you ask
on an exam and it is different than a behavioral repertoire
One of the reasons I like this text so much is that it is clear
that the authors are not from this old school

This will become more obvious when you read the material related
to ability testing
NFE: Back to construct validity
70

But, back to the question you are asking with construct
validity:
Does the test actually measure the “construct” you think it is
measuring?
 Is your measure of extroversion really measuring
extroversion?
 Is your measure of creativity really measuring
creativity?
Is your measure of ability to work with others
(agreeableness) really measuring the ability to work with
others?
NFE: Construct validity, cont.
71




You construct a test
You correlate your test with other tests that supposedly
measure the same thing (or a very similar construct) and
other measures that might get at that construct
Correlations are not going to be perfect because your
measure is not measuring exactly the same thing as those
other measures, but should be reasonably correlated with
those measures
Continue to do that until you have pretty good evidence
that your test is indeed measuring what it is supposed to be
measuring
NFE: Construct validity, cont.
72





But notice, for validation purposes, you are NOT done yet
You have evidence that the test is supposedly measuring
what you say it is, but
You still need to conduct a criterion-related validity study to
determine whether the test is related to the job
Thus, you end up doing a lot of time-consuming work
The ONLY reason you would do this was if you could not
locate a test that measured what you want and had to
create your own (not likely, by the way)