Review of Faking
in Personnel Selection
Michael A. McDaniel
Virginia Commonwealth University
mamcdani@vcu.edu
Deborah L. Whetzel
Human Resources Research Organization
dwhetzel@humrro.org
Chris D. Fluckinger
University of Akron
cdf12@uakron.edu
Prepared for:
International Workshop on “Emerging Frameworks and Issues for S&T Recruitments”
Society for Reliability Engineering, Quality and Operations Management (SREQOM)
Delhi, India
September, 2008

We note that Chris D. Fluckinger is the senior
author of our book chapter associated with this
conference. Although not present at the
conference, his contributions to this
presentation were substantial.
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Goal of this Presentation

Provide practitioners and researchers with
a solid understanding of the practical
issues related to faking in test delivery and
assessment.
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Overview
Typical vs. maximal performance
 The usefulness of different strategies to
identify faking
 How faking creates challenges to test
delivery and measurement
 Review and critique of common strategies
to combat faking

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Faking


Faking is a conscious effort to improve one’s
score on a selection instrument.
Faking has been described using various terms
including:
 Response
distortion
 Social desirability
 Impression management
 Intentional distortion, and
 Self enhancement

Hough, Eaton, Dunnette, Kamp, & McCloy (1990); Lautenschlager, (1994); Ones,
Viswesvaran & Korbin (1995).
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Maximal vs. Typical Performance

Faking can be understood by comparing
the distinction between maximal and
typical performance.
 Cronbach,

(1984)
This distinction is useful in understanding
faking.
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Maximal Performance

Maximal performance tests assess how
respondents perform when doing their
best.
 A mathematics
test of subtraction is an
assessment of maximal performance in that
one is motivated to subtract numbers as
accurately as one is able.
 Cognitive ability and job knowledge tests are
also maximal performance measures.
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Maximal Performance



In high stakes testing, such as employment
testing, people are motivated to do their best,
that is, to provide their maximal performance.
In high stakes testing, both those answering
honestly and those seeking to fake have the
same motivation: Give the correct answer.
One can guess on a maximal performance test
but one cannot fake.
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Maximal Performance

Maximal performance tests do not have
faking problems because the rules of the
test (make yourself look good by giving the
correct answer) and the rules of the testing
situation (make yourself look good by
giving the correct answer) are the same.
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Typical Performance


In typical performance tests, the rules of the test
are to report how one typically behaves.
In personality tests, the instructions are usually
like this:
 Please
use the rating scale below to describe how
accurately each statement describes you. Describe
yourself as you generally are now, not as you wish to
be in the future. Describe yourself as you honestly
see yourself.
Adapted from http://ipip.ori.org/newIPIPinstructions.htm
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Typical Performance



Thus, in a typical performance test, if one is lazy
and undependable, one is asked to report on the
test that one is lazy and undependable.
The rules of the test (describe how you typically
behave) contradict the rules of the testing
situation (make yourself look good by giving the
correct answer).
This contradiction makes faking likely.
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Typical Performance



If one who is lazy and undependable, answers
honestly, one will do poorly on the test.
If one who is lazy and undependable fakes, the
respondent reports that they industrious and
dependable. The respondent who fakes will do
well on the test.
Example: McDaniel’s messy desk
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Typical Performance

Thus, one can improve one’s score on a
personality test by ignoring the rules of the
test (describe how you typically behave)
and by following the rules of the testing
situation (make yourself look good by
giving the correct answer).
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Typical Performance

On typical performance tests, it is easy to know
the correct responses:
 Dependable
 Agreeable
 Emotionally

stable
Thus, it is easy to fake on typical performance
measures, such as personality tests, and one
can dramatically improve one’s score through
faking.
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How much faking is there?

Over two-thirds (68%) members of the Society
for Human Resource Management (SHRM)
thought that integrity tests were not useful
because they were susceptible to faking.
 Rynes,

Similarly, 70% of professional assessors believe
that faking is a serious obstacle to
measurement.
 Robie,

Brown & Colbert (2002)
Tuzinski & Bly (2006)
These results suggest that there is frequent
faking in testing situations.
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How much faking is there?
There is some emerging evidence that
patterns exist regarding the proportion of
fakers in a given sample.
 Specifically, converging evidence—though
tentative—indicates that approximately
50% of a sample typically will not fake,
with most of the rest being slight fakers,
and a select few being extreme fakers.

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How much faking is there?

One study found that 30-50% of applicants elevated their
scores compared to later honest ratings.


There is also self-reported survey evidence that 65% of
people say they would not fake an assessment, with
17% unsure and 17% indicating they would fake.


Griffeth et al. (2005)
Rees & Metcalfe (2003)
None of this is encouraging for practitioners, because
the presence of moderate numbers of fakers, particularly
small numbers of extreme fakers, presents significant
problems when attempting to select the best applicants.

Komar (2008)
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Personality tests are big business

Over a third of US corporations use
personality testing, and the industry takes
in nearly $500 million in annual revenue.
 Rothstein
& Goffin (2006)
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Stop using personality tests?


The fact that applicants may be highly motivated
to fake in order to gain employment has raised
many questions as to the usefulness of noncognitive measures.
Some have even gone far enough to suggest
that personality measurement should not be
used for employee selection.
 Murphy
& Dzieweczynski (2005)
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But personality predicts

Personality tests predict important work
outcomes, such as job performance and
training performance.
 Barrick,
Mount & Judge, 2001; Bobko, Roth &
Potosky, 1999; Hough & Furnham, 2003; Schmidt &
Hunter, 1998.
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Predict even with faking
Personality measures predict work
outcomes, even under conditions where
faking is likely.
 Rothstein and Goffin state that there are
“abundant grounds for optimism that the
usefulness of personality testing in
personnel selection is not neutralized by
faking” (p. 166).

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Faking still causes problems

Even though personality measures often
produce moderate predictive validities,
there are a number of other ways that
faking can cause problems, including:
 the
construct validity of measures
 changes in the rank-order of who is selected.
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Evidence of faking
Evidence of faking

The concept of faking is relatively
straightforward:
 People
engage in impression management
and actively try to make themselves appear to
have more desirable traits than they actually
possess.

However, identifying actual faking
behaviors in a statistical sense has proven
to be exceedingly difficult.
 Hough
& Oswald (2005)
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Faking shows itself in various ways

Attempts to fake can show up in a number of
statistical indicators:
 test
means
 social desirability scales
 criterion-related validity
 actual or simulated hiring decisions
 construct validity.

There is ample evidence that faking likely
influences most of these crucial test properties
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Social desirability as faking

The construct of social desirability states that the
tendency to manage the impression one maintains with
others is a stable individual difference that can be
measured using a traditional, Likert-style, self-report
survey.


Paulhus & John (1998)
Social desirability items are unlikely virtues, that is,
behaviors that we recognize as good but that no one
usually does:



I have never been angry
I pick up trash off the street when I see it.
I am always nice to everyone
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Social desirability as faking

Applicants for a job had higher social desirability
scores than incumbents, which was interpreted
as evidence that the applicants were faking.
 Rosse,

Stecher, Miller, & Levine (1998)
The initial view regarding social desirability from
an applied perspective was that it could be
measured in a selection context and used to
correct, or adjust, the non-cognitive scores
included in the test.
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Social desirability as faking


Social desirability does not function as frequently
theorized.
A meta-analysis showed that social desirability
does not account for variance in the personalityperformance relationship.
 Ones,

Viswesvaran and Reiss (1996)
This means that knowledge of a person’s level of
social desirability will not improve the
measurement of that person’s standing on a
non-cognitive trait.
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Social desirability as faking


Stated another way, this means that one cannot
correct a person’s personality test score for
social desirability to improve prediction.
Applicants often fake in ways that are not likely
to be detected by social desirability scores.
 Alliger,
Lilienfeld & Mitchell (1996); Zickar & Robie,
(1999)

Summary: Social desirability is a poor indicator
of applicant faking behavior.
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Mean difference as faking
Faking is apparent when one compares
responses of groups of people who take a
test under different instructions
 Test scores under fake-good instructions
lead to higher test means than scores
under honest instructions (d ≈ .6 across
Big 5 personality dimensions).

 Viswesvaran
& Ones (1999)
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Mean difference as faking


This pattern is similar when comparing actual
applicants and incumbents
The largest effects are found for the traditionally
most predictive personality dimensions in
personnel selection, conscientiousness (d = .45)
and emotional stability (d = .44).
 Birkeland,
Manson, Kisamore, Brannick & Smith
(2006)

Integrity test means shows the same pattern of
increased means in faking conditions (d = .36 to
1.02).
 Alliger
& Dwight (2000)
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Mean difference as faking


Thus, people have the highest means in
experimental, fake-good designs and somewhat
lower means in applicant settings, and these
means are nearly always higher than
honest/incumbent conditions.
These are the most consistent findings in faking
research, and they are often taken as the most
persuasive evidence that faking occurs.
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Mean difference as faking

Although the mean differences between
faking and honest groups permits one to
conclude that faking occurs, it is of little
help in identifying which applicants are
faking.
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Criterion-related validity and faking
Criterion-related validity is the correlation
between a test and an important work
outcome, such as job performance.
 It is logical to assume that as applicants
fake more, the test will be less able to
predict important work outcomes.

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Criterion-related validity and faking

Students’ conscientiousness ratings (measured with
personality and biodata instruments) were much less
predictive of supervisor ratings when they completed the
measures under fake-good instructions.


The general pattern in applied samples is similar, as
predictive validity is highest in incumbent (supposedly
honest) samples, slightly lower for applicants, and
drastically lower for fake-good directions.


Douglas, McDaniel and Snell (1996)
Hough, 1998
These findings are commonly interpreted as supporting
the hypothesis that faking may lower criterion-related
validity, but it often does not do so drastically.
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Criterion-related validity and faking


There are a number of caveats to this general
pattern regarding predictive validity.
One is situation strength: when tests are
administered in ways that restrict natural
variation, criterion-related validity will drop.
 Beatty,

Cleveland & Murphy (2001)
For example, if an organization clearly
advertises that it only hires the most
conscientious people, then applicants are more
likely to fake to appear more conscientious.
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Criterion-related validity and faking


Another caveat is the number of people who
fake.
A Monte Carlo simulation found that the bestcase scenario for faking is an all-or-nothing
proposition: validity is retained with no fakers or
many fakers, but if there is a small minority of
fakers present, they are likely to be rewarded,
thus dragging overall test validity down.
 Komar,
Brown, Komar & Robie (2008)
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Criterion-related validity and faking

A final caveat is that the criterion-related validity of the
test as a whole may not be sensitive to changes in the
rank-ordering of applicants.


This assumption was tested by rank-ordering
participants from two conditions (honest and fake-good),
and then dividing the distribution into thirds.


Komar et al., (2008)
Mueller-Hanson, Heggestad and Thornton (2003)
The results indicated that the top third, which included a
high percentage of participants who were given faking
instructions, had low validity (r = .07), while the bottom
third produced high validity (r = .45).
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Criterion-related validity and faking

Thus, a criterion-related validity study may
show that the test predicts job
performance. However, the test may not
predict well for the top scoring individuals
because these are the individuals who
fake.
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Selection decisions and faking
The last slide suggested that those who
fake may cluster at the top of the score
list.
 This introduces the topic of selection
decisions and faking.

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Selection decisions and faking

It is a common finding that people who fake —
identified by higher social desirability scores or
by higher proportions of those from a faking
condition— will rise to the top of the selection
distribution and increase their probability of
being hired.
 Mueller-Hanson

et al. (2003); Rosse et al., (1998)
This situation worsens as the selection ratio is
lowered (fewer people are selected), because
more of them are likely to be fakers.
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Selection decisions and faking
One study obtained applicant personality
scores and then honest scores one month
later.
 Out of 60 participants, one individual who
was ranked #4 for the applicant test
dropped to #52 for the honest test,
indicating a large amount of faking.

 Griffeth,
Chmielowski and Yoshita (2005)
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Selection decisions and faking
Numerous additional studies have
provided similar findings, suggesting that
the rank order of applicants will change
considerably under different motivational
and instructional conditions.
 This pattern is usually attributed to faking
behavior, but it can also be partly
explained by random or chance variation.

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Selection decisions and faking
People might score higher or lower on a
second test administration due to random
factors (e.g., feeling ill).
 Regardless, these consistent findings
demand that users of non-cognitive tests
cannot simply rely on a test’s predictive
validity to justify its utility as a selection
device.

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Construct validity and faking
The construct validity of a test concerns
the internal structure and reliable
relationships with other variables.
 Construct validity helps one to understand
what the test measures and what it does
not.

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Construct validity and faking
Construct validity is often overlooked in
favor of criterion-related validity.
 However, construct validity is crucially
important regarding the quality of what is
measured.
 Construct validity can also help us
understand faking.

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Construct validity and faking



Factor analysis is a statistical method to help determine
constructs measured by a test.
Research indicates that construct validity does indeed
drop when faking is likely present.
The factor structure of non-cognitive tests, especially
personality, tends to degrade when applicants are
compared with incumbents, as an extra factor often
emerges with each item loading on that factor in addition
to loading on the hypothesized factors.

Zickar & Robie (1999); Cellar, Miller, Doverspike & Klawsky
(1996)
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Construct validity and faking

This means that the non-cognitive
constructs actually change under faking
conditions, shedding some doubt as to
how similar they remain to the intended,
less-biased constructs.
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Summary of Faking Studies
Applicants can fake and some do fake.
 Evidence for faking can be seen in various
types of studies.
 But there is no good technology for
differentiating the fakers from the honest
respondents.

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Practical issues in
test delivery
Properties of the selection system

Two key aspects of selection systems are
particularly relevant to the issue of faking:
 Multiple-hurdle
vs. compensatory systems
 Use and appropriate setting of cut scores
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Properties of the selection system
Multiple-hurdle vs. compensatory systems
A multiple-hurdle system involves a series
of stages that an applicant must pass
through to ultimately be hired for the job.
 This usually involves setting cut scores—a
line below which applicants are removed
from the pool—at each step (or for each
test in a selection battery).

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Properties of the selection system
Multiple-hurdle vs. compensatory systems

A compensatory system, on the other
hand, typically involves an overall score
that is computed for each applicant,
meaning that a high score for one test can
compensate for a low score on another.
 Bott,
O’Connell, Ramakrishnan & Doverspike, (2007)
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Properties of the selection system
Multiple-hurdle vs. compensatory systems



A common validation procedure involves setting
cut scores based on incumbent data and then
applying that standard to applicants.
The higher means in applicant groups could
result in systematic bias in the cut scores.
Basically, since there is faking in applicant
samples, using the cut score determined from
incumbent data will result in too many applicants
passing the cut score.
 Bott
et al. (2007)
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Properties of the selection system
Multiple-hurdle vs. compensatory systems

Personality tests may best be used from a select-out
versus the traditional select-in perspective.


Mueller-Hanson et al. (2003)
This means that the non-cognitive measure’s primary
purpose would be to weed out the very undesirable
candidates rather than to identify the applicants with the
highest level of the trait.



Don’t hire the people who state that they are lazy and
undependable
But know that many of the people who score well on the
personality test are also lazy and undependable
Thus, the goal of the personality test is to reject those who are
lazy and undependable and willing to admit it.
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Properties of the selection system
Multiple-hurdle vs. compensatory systems



Using a personality test or other non-cognitive measures
as a “screen-out” allows many more applicants to pass
the hurdle, thereby increasing the potential cost of the
system.
One still needs to screen the remaining applicants.
Select-out may be a reasonable option under conditions
of:



A high selection ratio (with many positions to fill per applicant)
Or low cost per test administered (such as unproctored internet
testing).
Practitioners have to carefully consider and justify how
the setting of cut scores matches with the goals and
constraints of different selection systems.
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Situational judgment tests with
knowledge instructions
As noted in a previous presentation at this
conference, situational judgment tests can
be administered with knowledge
instructions.
 Knowledge instructions ask the applicants
to identify the best response or to rate all
responses for effectiveness

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Situational judgment tests with
knowledge instructions

Knowledge instructions for situational
judgment tests should make them
resistant to faking.
 McDaniel,
Hartman, Whetzel, & Grubb (2007);
McDaniel & Nguyen (2001); Nguyen, Biderman, &
McDaniel (2005)
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Situational judgment tests with
knowledge instructions

Although resistant to faking, these tests
still measure non-cognitive traits,
specifically:
 Conscientiousness
 Agreeableness
 Emotional

stability
McDaniel, Hartman, Whetzel, & Grubb (2007)
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Situational judgment tests with
knowledge instructions
Thus, situational judgment tests hold great
promise for measuring non-cognitive traits
while reducing, and perhaps eliminating,
faking.
 There are some limitations.

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Situational judgment tests with
knowledge instructions

Limitations
 It
is hard to target a situational judgment test
to a particular construct
 It is hard to build homogenous scales
With personality tests, one can easily build a scale
to measure conscientiousness and another to
measure agreeableness
 Situational judgment tests seldom have clear
subtest scales

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Faking and cognitive ability

The ability to fake may be related to
cognitive ability such that those who are
more intelligent can fake better.
 The

little literature on this is contradictory.
If faking is dependent on cognitive ability,
then faking should increase the correlation
between personality and cognitive ability.
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Faking and cognitive ability


One advantage of non-cognitive tests is that
they show smaller mean differences across
ethnic groups.
If the ethnic group differences are due to mean
differences in cognitive ability, and if faking
increases the correlation between personality
and cognitive ability, faking should make the
ethnic group differences in personality larger.
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Faking and cultural differences
Almost all faking research is done with
U.S. samples.
 The prevalence of faking might be
substantially larger in other cultures.
 For example, in cultures where bribery is a
common business practice, one might
expect more faking.

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Potential solutions
to faking
Social desirability scales
The literature is very clear that social
desirability scales do not help in identifying
fakers.
 Statistical corrections based on social
desirability scales do not improve validity.




Ellingson, Sackett and Hough (1999)
Ones, Viswesvaran and Reiss (1996)
Schmitt & Oswald (2006)
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Frame of reference

The rationale behind frame of reference
testing is to design tests that encourage
test takers to focus on their behavior in a
particular setting (e.g., work).
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Frame of reference

An example of frame of reference is the
addition of the phrase “at work” at the end
of each items.
 Typical
item: I am dependable
 Frame of reference item: I am dependable at
work.
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Frame of reference

There is some evidence that frame of
reference testing may increase validity.


Bing, Whanger, Davison & VanHook (2004); Hunthausen,
Truxillo, Bauer & Hammer (2003)
However, there is no evidence that frame
of reference testing reduces faking
behavior.
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Test instructions: Coaching



If we want people to respond to our tests in a
certain way, we can simply tell them via test
instructions.
Coaching is one kind of instruction, usually in the
form of a vignette or example describing how to
approach an item in a socially desirable way.
Coaching predictably leads to faking behavior
(as evidenced by higher test means) and is
certainly a problem as advice to “beat” noncognitive tests circulates around the internet.
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Test instructions: Warning

Another popular strategy is to warn test
takers that they will be identified and
removed from the selection pool if they
fake (known as a warning of identification
and consequences).
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Test instructions: Warning

A meta-analysis indicated that warnings
generally lower test means over standard
instructions (d = .23), although there was
considerable variability in the direction and
magnitude of effects in the studies
included.
 Dwight
and Donovan (2003)
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Test instructions: Warning

Problems:
 Warnings
may increase the correlation
between the personality scales and cognitive
ability.

Vasilopoulos et al. (2005)
 Since
one can not actually identify the fakers,
it is dishonest to warn test-takers that fakers
can indeed be identified.

Zickar & Robie (1999)
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Test instructions: Warning
If most applicants heed the warning and
do not fake, those who do fake may more
easily obtain higher test scores.
 Thus, warnings are admittedly an
imperfect method for combating faking,
and more research is needed to determine
the extent of their utility.

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Get data other than self-report


Personality and other non-cognitive constructs
are often evaluated for selection purposes
through ratings of others, including interviews
and assessment centers.
Approximately 35% of interviews explicitly
measure non-cognitive constructs, such as
personality and social skills, according to metaanalytic evidence.

Huffcutt, Conway, Roth & Stone (2001)
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Get data other than self-report

Similarly, many common assessment
center dimensions involve non-cognitive
aspects, including communication and
influencing others.
 Arthur,
Day, McNelly & Edens (2003)
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Get data other than self-report
Little faking and impression management
research has examined faking in
interviews and assessment centers.
 However, it is logical that those who would
fake in a personality inventory would also
fake in an interview or an assessment
center.

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Forced-choice measures
Item 1
Choose one item that is Most like you, and one
item that is Least like you
Most Like Me
Least Like Me
Get irritated easily.
Have little to say.
Enjoy thinking about things.
Know how to comfort others.
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Forced-choice measures


Forced-choice measures differ from Likert-type
scales because they take equally desirable
items (desirability usually determined by
independent raters) and force the respondent to
choose.
Forced-choice has costs:
 Abandoning
the interval-level scale of measurement
 Abandoning the clearer construct scaling that Likert
measures offer.
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Forced-choice measures


Whether the benefits of forced-choice formats,
such as potentially reducing faking, justify these
costs is questionable.
The effect of forced-choice on test means is
unclear, as some studies show higher means of
forced-choice compared with Likert measures
and others indicate lower means.
 Heggestad,
Morrison, Reeve & McCloy, (2006);
Vasilopoulos, Cucina, Dyomina, Morewitz & Reilly
(2006)
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Forced-choice measures

Research on the effect of forced-choice on
selection decisions used items in both a
forced-choice and Likert format under
pseudo-applicant instructions (pretend you
are applying for a job).
 Heggestad
et al. (2006)
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Forced-choice measures



They compared the rank-order produced by both tests to
an honest condition using a different personality
measure.
Results showed few differences in the rank-orders
between the measures, offering preliminary evidence
that forced-choice does not improve selection decisions.
In summary, forced-choice tests do not necessarily
reduce faking, and the statistical and conceptual
limitations associated with their use probably does not
justify replacing traditional non-cognitive test formats.
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Recommendations
for Practice
Avoid corrections


Little evidence exists that social desirability
scales or lie scales can identify faking.
Many tests include lie scales with instructions
about how to correct scores based on lie scales,
with the justification that corrections will improve
test validity.
 Rothstein

& Goffin (2006)
There is no evidence to support this assertion,
rendering corrections a largely indefensible
strategy.
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Specify how non-cognitive measures fit
the goals of the selection system

Given the consistent effect of faking on
test means, faking will affect cut scores
and who is selected in both compensatory
and multiple hurdle systems.


Bott et al. (2007)
Cut scores may have to be adjusted
upward if they are set based on incumbent
scores.
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Specify how non-cognitive measures fit
the goals of the selection system

The select-out strategy is an option.
 Reject
applicants who are willing to admit that
they are lazy and undependable
 Screen the remaining applicants with a
maximal performance measure that is fakingfree or faking-resistant.
 Select-out is a good strategy when the
selection ratio is high (i.e., you will hire most
of those who apply).
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Recognize that criterion-related
validity may say little about faking
It is common to have a useful level of
validity for the test, when known faking is
present.
 However, the fakers are represented in
greater proportions at the high end of the
test scores.
 The validity may be much worse among
these applicants.

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Manipulate the motivation of the
applicants

If applicants are given information about the job to which
they are applying, they can fake their scores toward that
stereotype.


Mahar, Cologon & Duck (1995)
On the other hand, if applicants are informed about the
potential consequences of poor fit, which faking could
realistically lead to during the placement phase, they
may be motivated to respond more honestly, and initial
research indicates that this may be true.

Nordlund & Snell (2006)
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Conclusion
Non-cognitive tests can be faked.
 Non-cognitive tests are faked.
 There is no method to eliminate faking.
 Consider using non-cognitive tests as
select-out screens

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Conclusion
Use maximal performance tests (cognitive
ability and job knowledge) to screen those
who remain.
 Consider measuring non-cognitive traits
with faking-resistant situational judgment
tests with knowledge instructions.

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References

References are in the book chapter.
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Thank you.
Questions??
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