What Is Beyond the Big Five? Plenty!
Sampo V. Paunonen
Douglas N. Jackson
University of Western Ontario
ABSTRACT In a recent analysis of personality data, Saucier and Goldberg
(1998) sought to answer the question, What is beyond the Big Five? Those
authors evaluated numerous clusters of English person-descriptive adjectives
that have been suspected of referring to non–Big Five dimensions of personality.
Their results led them to conclude that most, if not all, traits of personality can
be adequately subsumed within the Big Five factor space. In contrast, our
reanalysis of Saucier and Goldberg’s own data, using a more realistic criterion
for deciding on whether a variable does or does not fall within a particular factor
space, contradicts their claim. We are led to the conclusion that there are plenty
of dimensions of behavior beyond the Big Five.
Few topics in contemporary psychology have generated as much research
and theoretical interest as has the Five-Factor Model of personality. That
model has been embraced not only by a personality psychologist, but by
researchers in clinical, industrial/organizational, and developmental psychology as well. The Five-Factor Model, of course, posits that there is a
structure to individual differences in human behavior, such that the traits
of personality can be reduced to five orthogonal factors of personality—the so-called Big Five.
This research was supported by the Social Sciences and Humanities Research Council
of Canada Research Grant 410-98-1555 to Sampo V. Paunonen. We thank Michael Ashton
and Kibeom Lee for their comments on this article.
Correspondence concerning this article should be addressed to Sampo V. Paunonen,
Department of Psychology, University of Western Ontario, London, Ontario N6A 5C2,
Canada.
Journal of Personality 68:5, October 2000.
Copyright © 2000 by Blackwell Publishers, 350 Main Street, Malden, MA 02148,
USA, and 108 Cowley Road, Oxford, OX4 1JF, UK.
822
Paunonen & Jackson
As noted by Saucier and Goldberg (1998), the Big Five factors
originated with studies of the structure underlying personality ratings,
ratings made using words taken from the English-language personality
lexicon. When personality adjectives are sampled from the language,
either exhaustively or randomly, and used to describe real people, they
tend to define five orthogonal clusters. The names applied to those
lexically based clusters, in decreasing order by size, are Extraversion,
Agreeableness, Conscientiousness, Emotional Stability versus Neuroticism, and Intellect or Imagination. Roughly the same five dimensions
tend to be found in the same order with impressive consistency across
different samples of subjects, different selections of personality adjectives, and even different cultures and language groups.
The Big Five factors of personality are thought to be important
precisely because they are big. According to the Lexical Hypothesis, the
words we have invented to describe individual differences in personality
are reflections of real human behaviors, and the number of words we
have invented is in direct proportion to the importance of the behavior
domain described. As Goldberg (1982) has said, “Those individual
differences that are most significant in the daily transactions of persons
with each other become encoded into their language. The more important
such a difference is, the more people will notice it and wish to talk of it,
with the result that eventually they will invent a word for it” (p. 204).
The discovery of the Big Five factors of personality in linguistic data
has subsequently led to the structural evaluation of questionnaires and
other personality instruments, instruments that may or may not be
purposely designed to measure those factors. Sometimes, however, the
lexical and nonlexical (i.e., questionnaire) factors have differed in morphology. For example, whereas the lexical studies typically find a factor
(the smallest) called Intellect, questionnaire-based measures have tended
to focus on a dimension (also the smallest) called Openness to Experience
(e.g., see Costa & McCrae, 1992). Other differences in Five-Factor
Models can also be noted (see reviews by Block, 1995; Digman, 1990;
John, 1990; McCrae & John, 1992).
The Saucier and Goldberg (1998) Analysis
Goldberg has presented, in some past publications, lists of words that can
be considered characteristic or prototypical of each of the lexical Big
Five, based on his extensive analyses of the factor structure underlying
Beyond the Big Five
823
person descriptors in the English language (e.g., Goldberg, 1982, 1990,
1992). As Saucier and Goldberg (1998) have observed, however, some
of the personality adjectives evaluated have not been closely aligned with
the traditional Big Five factors in certain studies. Those authors, in fact,
identified 53 such adjective clusters, each relatively homogeneous but
suspected by some as being potentially outside the domain of the traditional lexical Big Five.
Saucier and Goldberg (1998) modified 21 of their 53 adjective clusters
to make them even more homogeneous and included all 74 groups of
words in their analysis. Their intent was to evaluate the extent to which
each cluster of words shows statistical allegiance to the lexical Big Five.
To do this, they administered the personality adjectives along with
traditional Big Five marker adjectives to subjects in a self-report format.
They then correlated scores on each of the 74 word clusters with scores
on each of the five factors. Their ultimate test of whether or not a
particular word cluster belonged within the space of the Big Five was to
compute a multiple correlation between that cluster and the five factor
measures. A word cluster that has much variance in common with one or
more of the Big Five would, of course, have a high multiple correlation
with those factors.
The 74 multiple correlations of Saucier and Goldberg’s word clusters with
their Big Five marker variables ranged from .09 to .67 with a mean of .38.
Using an arbitrary cutoff score of .30 to decide whether a particular word
cluster was or was not within the five-factor domain, those authors identified
some person descriptor clusters, mainly related to physical characteristics,
as being beyond the Big Five. Those clusters, each having a multiple
correlation with the factors of less than .30, included words referring to a
person’s height, weight, age, and physical attractiveness. Importantly, only
one personality-relevant word cluster was likewise judged not to be within
the bounds of the traditional Big Five, and it was related to religiosity,
containing words such as religious, devout, and reverent. With regard to
religiosity, however, Saucier and Goldberg claimed that “many might classify this cluster as reflecting individual differences in attitudes or ideology,
rather than personality” (p. 506).
Saucier and Goldberg’s Data Revisited
Saucier and Goldberg (1998) have done a commendable job of identifying clusters of personality adjectives that appear, at least at face value,
824
Paunonen & Jackson
not to have a strong relation to any of the Big Five factors. But their
analysis led them to the conclusion that almost all of those personality
variables are, in fact, related to the Big Five nontrivially. Upon our initial
read of their article, we found this conclusion a curious one, given the
nature of some of the person descriptors involved (see Saucier and
Goldberg, 1998, Table 1). Consider, for example, the three dimensions
masculine versus feminine, witty and humorous, cunning and sly. None
of these seems to belong firmly to any Big Five factor. Saucier and
Goldberg, however, concluded that all three dimensions do indeed fit into
the space of the Big Five. But notice that a cluster of person descriptive
adjectives related to one’s financial wealth (i.e., being prosperous, rich,
and well-to-do versus being poor), by Saucier and Goldberg’s own
criterion, was found to be more a part of the Big Five factors than were
dimensions related to being masculine-feminine, or being witty and
humorous, or being cunning and sly (1998, Table 2). Curious indeed.
As we are about to describe, our consideration of Saucier and Goldberg’s (1998) results has led us to the conclusion that many of the
variables assessed in that study do not have a lot in common with the
traditional lexical Big Five. But this conclusion stands in direct contrast
to that of Saucier and Goldberg. The primary reason for this discrepancy
is to be found in the choice of the statistical criterion for what constitutes
a Big Five indicator. As we explain below, we take issue with Saucier and
Goldberg’s criterion as being much too liberal.
Table 2 in Saucier and Goldberg’s (1998) article shows the correlations
between each of their 74 adjective clusters and each of their Big Five
factor measures. Now note how those correlations are similar to factor
loadings, being the correlations between variables and factors as found
in a normal factor structure matrix. In fact, those correlations are properly
interpreted as factor loadings in an extension analysis (see Dwyer, 1937;
Gorsuch, 1983; Mosier, 1938). An extension analysis refers to the technique of correlating variables with factors when the variables themselves
were not part of the analysis that produced the factors, which is exactly
what Saucier and Goldberg have done.
Gorsuch (1983) mentioned a good reason for doing an extension
analysis that is particularly pertinent to the present discussion.
Extension analysis may be needed to test a hypothesis regarding the
nature of a particular factor. A well-replicated factor may be hypothesized to be that which is measured by variable Z. To include
Beyond the Big Five
825
variable Z in an exploratory factor analysis would usually allow it
to help define the factor. Because this includes the possibility of
capitalizing on chance, it would be better to determine variable Z’s
relationship to the factor when the factor is based solely on the other
variables. Then variable Z is correlated independently with the
factor. (p. 237)
Thus, Saucier and Goldberg (1998) were correct not to include their 74
adjective clusters in a factor analysis with Big Five marker variables.
Their goal was to determine the extent to which those clusters, thought
to be questionable in this context, fall in the space of the Big Five. Their
goal was not to use those clusters to help determine the space itself (see
also Paunonen & Jackson, 1996).
As already mentioned, the extension loadings reported by Saucier and
Goldberg (1998) in their Table 2 are simply factor loadings that one might
see in a typical factor analysis. Such extension loadings, however, will
generally be slightly lower in magnitude than will factor loadings in
which the variables have been included in the factor analysis. The reason
is that, with a typical variable-factor correlation, the factor contains the
variable itself as part of the linear composite, inflating the correlation
somewhat (this is the capitalization on chance referred to in Gorsuch’s
quote above). This difference in value between an extension loading and
a regular factor loading for a variable, however, should not be great if
that variable is one of many that define the factor.
How does one normally determine, in a regular factor analysis,
whether or not a particular variable falls in the space of the common
factors extracted? First, one would naturally look at the size of the largest
loading for the variable to see whether or not it clearly defines a particular
factor. As noted by Zwick and Velicer (1982), loadings of less than about
.40, and certainly of less than .30, would hardly qualify as salient
loadings. What about Saucier and Goldberg’s extension loadings? Of 74
variables, three had loadings of .50 or greater, three had loadings of .40
to .50, and 18 had loadings of .30 to .40. That leaves 50 personality word
clusters with factor loadings so small in size that one could not reasonably
consider them to define a particular factor of the Big Five exclusively.1
1. Saucier and Goldberg (1998) also cited Zwick and Velicer, but in defense of their
choice of a .30 cutoff multiple correlation as indicating whether or not a variable falls
within the space of the Big Five factors. In this context, they wrote “Zwick and Velicer
(1982) noted that loadings below .30 or .40 are usually ignored in applications of principal
826
Paunonen & Jackson
Now, a variable might have no salient loading on any one factor but,
instead, might split across two or more factors. Such a variable could still
be considered to fall within the space of the common dimensions,
representing a blend of multiple factors. But before such an interpretation
is warranted, one must eliminate the possibility that the variable has
projections into higher dimensionalities beyond the common factor
space, and the way to do that is to calculate its communality. The
communality of a variable is computed as the sum of its squared factor
loadings taken across the common factors. But note that this is also the
computation for the (squared) multiple correlation between the variable
and the (orthogonal) factors (Harman, 1976, p. 83). In fact, what Saucier
and Goldberg reported as multiple correlations in their Table 2 are no
more than the unsquared communalities of the variables in their Big Five
factor space.
Normally one would not consider the multiple correlation between a
variable and a set of factors in deciding whether that variable falls within
the common factor space. Instead, one would evaluate the variable’s
communality. So what do Saucier and Goldberg’s (1998) personality
variables look like in that context? By squaring the multiple correlations
of their 74 adjective clusters with their Big Five factors, we find variable
communalities ranging from a .01 to .45 with a mean of only .16. Recall
also their cutoff multiple correlation value of .30 for determining whether
a variable does or does not fall within the space of the Big Five. That
value corresponds to communality of only .09.
We submit that a communality of .09 is not of sufficient magnitude to
support the claim that the variable falls within the factor space in
question. Such a variable would have only 9% of its variance being due
to the factors but 91% of its variance being due to some combination of
error variance and specific variance. (The error and specific variance
components of a variable are collectively referred to as its uniqueness
and, together with its communality, make up its total variance.) But there
components analysis” (p. 514). The implication of their statement is that the variablefactors multiple correlations they computed are no different than factor loadings, and the
same criteria that are used to evaluate the one can be applied to the other. As we are about
to demonstrate, however, the multiple correlation of a variable with a set of factors is not
the variable’s factor loading. The variable’s factor loading is its simple correlation with
a single factor. And, as far as Saucier and Goldberg’s extension factor loadings are
concerned (Table 2), the large majority of those simple correlations do not even come
close to meeting Zwick and Velicer’s .30–.40 cutoff for defining the factors in question.
Beyond the Big Five
827
is more. Knowing the communalities and reliabilities of each of Saucier
and Goldberg’s 74 clusters permits us to partition those variables’ variances into their separate common, specific, and error components (see
Harman, 1976, p. 20). As mentioned, the proportion of total variance in
common with the Big Five factors varied from 1% to 45% for the 74
variable clusters, with a mean of 16%. The specificities of those variables,
in contrast, can be computed as ranging from 21% to 88% with a mean
of 58%. What does this mean? It means that the uniquenesses of the
variables are not all due to error variance. It means that those variables
with small communalities and large specificities have substantial projections into dimensions beyond the Big Five.
Possible Outliers to the Big Five
We next decided to reevaluate Saucier and Goldberg’s 74 clusters in terms
of possible consistencies in personality content, but content that might
be beyond the Big Five. To do this we first eliminated from consideration
variables having to do with physical characteristics (e.g., short-tall),
demographics (e.g., employed-unemployed), low base rate undesirable
behaviors (e.g., evil, cruel), and variables otherwise not clearly related
to traditional personality traits (e.g., lucky-unlucky). We also relaxed
somewhat Saucier and Goldberg’s criterion of a .09 communality in
deciding on whether a variable does or does not fall outside the domain
of the Big Five factors. We chose a more reasonable, but still liberal,
communality of .20 as our criterion. (We discuss these arbitrary cutoffs
later in this article.)
Our reevaluation of Saucier and Goldberg’s (1998) 74 adjective clusters led us to identify 26 of them as appearing to constitute meaningful
personality dimensions that, in the present data, all had communalities
of less than .20 while having high reliabilities. The mean communality
of the 26 clusters was, in fact, only .13, but with a mean reliability of .72.
These figures indicate 26 internally consistent clusters of variables
having nontrivial projections into a hyperspace that is beyond the five
dimensions evaluated by Saucier and Goldberg.
Some of the 26 clusters we identified as relatively independent of the
Big Five obviously overlapped with one another. In fact, they appeared
to us to describe perhaps nine distinguishable bipolar dimensions of
personality. We describe these dimensions below with reference to one
828
Paunonen & Jackson
pole only and in no particular order. The numbers in parentheses refer to
Saucier and Goldberg’s (1998) word cluster identifiers.
1. Religious, devout, reverent. This set of four adjective clusters (nos.
9, 9r, 14, 20) had the lowest communality of all the groups we
identified in this section. Those four clusters had a mean communality of only .07. Saucier and Goldberg (1998) have admitted that
the dimension of religiosity is probably the most likely candidate
in their set of variables to reside beyond the traditional Big Five
personality factors (see also Goldberg, 1990).
2. Sly, deceptive, manipulative. Six clusters of adjectives (nos. 12, 12r,
18, 18r, 21, 21r) related to this personality dimension had a mean
communality of .13 in the present five-factor space. Interestingly,
several studies in the past with the Social Astuteness scale of the
Jackson Personality Inventory–Revised (JPI-R; Jackson, 1994)
have supported the notion that this domain of behaviors does not fit
well into the traditional nonlexical Big Five factor space (see
Ashton, Jackson, Helmes, & Paunonen, 1998; Detwiler &
Ramanaiah, 1996; Paunonen & Jackson, 1996).
3. Honest, ethical, moral. Three clusters of variables (nos. 1, 1r, 26)
related to honesty had a mean communality of .11. There is substantial independent evidence that behaviors related to this dimension of personality are largely orthogonal to the traditional Big Five
factors. Ashton, Lee, and Son (in press), for example, have compiled the results of several cross-cultural studies showing that
honesty might best be considered another “big” personality factor
in its own right, being at least as large as the Intellect factor in many
lexical studies (see also Peabody, 1987).
4. Sexy, sensual, erotic. The three clusters (nos. 7, 15, 33) defining
this content dimension had a mean communality of .13. As noted
by Saucier and Goldberg (1998), Buss (1996) has already suggested
that variables related to this class of behaviors do not fit well within
the Big Five personality factors.
5. Thrifty, frugal, miserly. Three variable clusters (nos. 4, 4r,
16) defined this dimension with a mean communality of .16.
Some additional evidence for the low communality within the
space of the Big Five of an adjective cluster comprised of the words
Beyond the Big Five
829
economical and thrifty can be found in an article by Goldberg
(1990, Table 4).
6. Conservative, traditional, down-to-earth. Four clusters of personality adjectives (nos. 10, 25, 41, 43) defining this domain had a mean
communality of .15. Note that this dimension of behavior is similar
to that measured by the JPI-R Traditional Values scale, a scale that
has had noticeably low communalities in some past nonlexical
studies of the Big Five (Ashton, Jackson, Helmes, & Paunonen,
1998; Paunonen & Jackson, 1996). This dimension has been implicated as a potential Big Five outlier even in other lexical studies
(see John, 1990).
7. Masculine-feminine. This one cluster (no. 35) was defined by those
two words alone, and had a communality of .13. Masculinityfemininity has been considered in the past as a dimension not
closely aligned with the Big Five (see Noller, Law, & Comrey, 1987;
Paunonen, 1993). Interestingly, Saucier and Goldberg (1998) had
two other clusters of person descriptors related to masculinity and
femininity (nos. 24, 24r), but they did not meet our criterion for
variables lying outside of the Big Five. Those other two clusters,
however, contained adjectives such as rough, coarse, and callous,
giving those dimensions relatively high loadings on Saucier and
Goldberg’s Agreeableness factor.
8. Egotistical, conceited, snobbish. A single cluster of adjectives
(no. 46) related to egocentric behaviors had a communality of .16.
Block (1995) has suggested the relative independence of this domain from the Big Five, a view that has been expressed by McCrae,
Costa, and Busch (1986).
9. Humorous, witty, amusing. This one cluster of adjectives (no. 44)
had a communality of only .13. Linguistic studies of the Dutch
language also have suggested that this dimension of personality
does not fit well within the Big Five personality factors (De Raad
& Hoskens, 1990). Also, one of Goldberg’s (1990) analyses of
self-ratings on the terms humorous and witty found that cluster
(Table 4), which he assigned to the Extraversion factor, to have a
mere .08 communality in the space of the Big Five.
830
Paunonen & Jackson
There is at least one other dimension of personality that we would add
to the list above—the dimension related to risk-taking or thrill-seeking
behaviors. Several nonlexical studies in the past have had difficulty in
placing this domain of behaviors within the space of the Big Five
(Ashton, Jackson, Helmes, & Paunonen, 1998; Jackson, Paunonen,
Fraboni, & Goffin, 1996; Paunonen & Jackson, 1996; Zuckerman, Kuhlman, Joireman, Teta, & Kraft, 1993). Curiously, that dimension was not
represented in Saucier and Goldberg’s (1998) set of 74 adjective clusters.
We do not intend to imply that the nine or ten dimensions described
above are mutually orthogonal. For example, some of those listed (e.g.,
deceptiveness and ethicalness) might be subsumed by a broader and more
general honesty factor (see Ashton, Lee, & Son, in press). Nor do we
intend to imply that those dimensions are as well represented in the
English language as are the traditional Big Five. Clearly they are not. But
whether or not that fact means that those dimensions are any less
important to understanding human behavior is debatable, and it is an issue
we raise again at the end of this article.
On the Sizes of Communalities
Saucier and Goldberg (1998) interpreted communalities of .09 or greater
as indicating variables that are important facets of a particular factor
space. We, instead, chose a more conservative communality criterion of
.20. The difference in interpretation based on the two criteria is that, in
the former case, one is led to conclude that there is little variance in
human behavior beyond the Big Five factor space, whereas, in the latter
case, one must conclude that there is much variance in behavior not
accounted for by those factors.
Is our communality criterion of .20 too conservative? We think not.
Consider our 26 clusters of personality-relevant adjectives that all met
this criterion, having a mean communality of .13. Twenty-four of those
clusters had communalities less than did two other clusters in the analysis
related to being rich or poor, the latter having a mean communality of
.17. Surely, personal wealth, even with a communality of .17, should not
be considered to be within the domain of the Big Five personality factors
for theoretical reasons alone. And if our supposition is correct, then it
follows that the other 24 behavior-based variables in the present analysis,
with lower communalities, are even less a part of the Big Five.
Beyond the Big Five
831
How do Saucier and Goldberg’s (1998) communalities compare to
factor results reported elsewhere? In the context of typical simple structure factor analyses, even when using established Big Five marker
variables, their values are very low. For example, Goldberg (1990) has
presented a list of 100 adjective clusters that purport to represent the core
of the Big Five factors of personality (see also Goldberg, 1992). The mean
communality of those marker variables in one of his analyses was .37
(Table 4, self-ratings). Compare that to the mean communality of only
.16 for the 74 clusters evaluated by Saucier and Goldberg (1998).
Recall that Saucier and Goldberg (1998) established an arbitrary cutoff
of .30 for the multiple correlation between a variable and the Big Five
factors in deciding whether or not the variable fell within the space of the
factors. But how does a multiple correlation of that size compare with a
multiple correlation based on other personality variables? By their standard, we can show that even some of the Big Five factors do not fall beyond
the space of the other four factors! Let’s consider a study by Goldberg
(1992), in which he calculated several estimates of the cross-correlations
of sets of aggregated Big Five marker variables. In Table 5 of that study,
he presented six Big Five factor-factor correlation matrices (based on
self-ratings, peer ratings, standardized scores, unstandardized scores,
etc.). Even if one takes the correlation matrix showing the most orthogonality among the Big Five factors (based on standardized self-ratings),
two of those factors are very close to meeting Saucier and Goldberg’s
criterion for not falling the beyond the space of the other four: Agreeableness has a multiple correlation of .28 with the other four factors, and
Conscientiousness has a multiple correlation of .29. Our example is the
best case scenario in Goldberg’s (1992) Table 5, and any of the other five
correlation matrices presented there yield even higher multiple correlations, far exceeding the .30 cutoff score. Thus, by Saucier and Goldberg’s
criterion, one is led to the conclusion that some of the Big Five factors
of personality, purportedly mutually orthogonal, do not themselves fall
beyond the space of the other four factors.2
2. Even questionnaire measures of the Big Five show such multicollinearity. Evaluation
of the NEO-PI-R (Costa & McCrae, 1992, Appendix F), for example, shows that three
of its Big Five Domain scales each have multiple correlations with the other four
exceeding .50, one has a multiple correlation exceeding .40, and one factor almost, but
not quite, reaches Saucier and Goldberg’s (1998) .30 cutoff criterion with a multiple
correlation of .28.
832
Paunonen & Jackson
A Final Word
We believe that there is much important variance in human behavior not
accounted for by the Big Five personality factors. This variance is
nonrandom and is related to internally consistent, theoretically meaningful classes of behavior that have, both historically and in Saucier and
Goldberg’s (1998) own data, failed to correlate highly with traditional
Big Five dimensions. One reason these domains of behavior have generally not been isolated empirically from typical Big Five lexical factors is
because, as we have shown here, such variables are often forced into the
five-factor space with remarkably trivial communalities (see also Saucier
& Goldberg, 1996). Another reason why the behavior domains we
described in this study are lacking in most lexical Big Five results is
probably because they are not well represented in the language of
personality. As such, they yield small factors in any analysis of linguistic
structure, at least relative to salient Big Five variables, and are thus
excluded from the final factor solution. But just because the words
describing a domain of behavior are relatively few in number, does that
mean that the domain is any less important than is some bigger one?
The Big Five factors no doubt represent prominent higher-order dimensions of individual differences that have become lavishly encoded in
the language. But if the language contains relatively few words to
describe a dimension of behavior, does that necessarily mean it is less
important in describing a person than is a larger dimension? Think of the
dimension of masculinity-femininity, referred to earlier in this article.
Neither word is found among Goldberg’s (1990) list of 339 trait adjectives purportedly representing the Big Five. The probable reason is that
there are few words in the English language that are gramatically synonyms or antonyms of masculine or feminine. Masculinity-femininity,
therefore, is unlikely to define its own factor in any comprehensive
analysis of the structure underlying personality descriptors because that
dimension, if it exists, will be a small one. As most criteria for factor
extraction and rotation are based on factor size, the masculinity-femininity
dimension will be excluded from the final solution. But is the excised
dimension not an important one? As far as masculinity-femininity is
concerned, some have viewed it as important enough to add to their
personality inventories, including the Comrey Scales (Comrey, 1970),
the California Psychological Inventory (Gough, 1987), and the Minnesota Multiphasic Personality Inventory (MMPI) (Hathaway & McKinley,
Beyond the Big Five
833
1967). Furthermore, evidence presented here and elsewhere (Noller,
Law, & Comrey, 1987) indicates that this dimension of behavior has a
substantial projection into a higher dimensionality than the five typically
evaluated.
Our view is that the ultimate test of whether a dimension of behavior
is important to the understanding of human behavior depends not on the
size of the factor in the language of personality, as the Lexical Hypothesis
would have us believe. The test should instead be one of incremental
utility. If one can identify theoretically meaningful, internally consistent
classes of behavior that are able to predict socially and personally
significant life criteria, then such personality dimensions are important
(e.g., see Ashton, Jackson, Paunonen, Helmes, & Rothstein, 1995; Mershon
& Gorsuch, 1988; Paunonen, 1998; Paunonen & Ashton, 2000;
Paunonen, Rothstein, & Jackson, 1999; Rothstein, Paunonen, Rush, &
King, 1994). Moreover, if such dimensions are able to account for
criterion variance not accounted for by the Big Five personality factors,
then those dimensions need to be considered separately in any comprehensive description of the determinants of human behavior.
REFERENCES
Ashton, M. C., Jackson, D. N., Helmes, E., & Paunonen, S. V. (1998). Joint factor analysis
of the Personality Research Form and the Jackson Personality Inventory? Journal of
Research in Personality, 32, 243–250.
Ashton, M. C., Jackson, D. N., Paunonen, S. V., Helmes, E., & Rothstein, M. G. (1995).
The criterion validity of broad factor scales versus specific trait scales. Journal of
Research in Personality, 29, 432–442.
Ashton, M. C., Lee, K., & Son (in press). Honesty as the sixth factor of personality:
Correlations with Machiavellianism, primary psychopathy, and social adroitness.
European Journal of Personality.
Block, J. (1995). A contrarian view of the Five-Factor Approach to personality description. Psychological Bulletin, 117, 187–215.
Buss, D. M. (1996). Social adaptation and five major factors of personality. In J. S. Wiggins (Ed.), Theoretical perspectives for the Five-Factor Model (pp. 180–207). New
York: Guilford Press.
Comrey, A. L. (1970). Manual for the Comrey Personality Scales. San Diego, CA:
Educational and Industrial Testing Service.
Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R)
and NEO Five-Factor Inventory (NEO-FFI) professional manual. Odessa, FL: Psychological Assessment Resources, Inc.
De Raad, B., & Hoskens, M. (1990). Personality-descriptive nouns. European Journal
of Personality, 4, 131–146.
834
Paunonen & Jackson
Detwiler, F. R. J., & Ramanaiah, N. V. (1996). Structure of the Jackson Personality
Inventory from the perspective of the five-factor model. Psychological Reports, 65,
947–950.
Digman, J. M. (1990). Personality structure: Emergence of the five-factor model. Annual
Review of Psychology, 41, 417–440.
Dwyer, P. S. (1937). The determination of factor loadings of a given test from the known
factor loadings of other tests. Psychometrika, 2, 173–178.
Goldberg, L. R. (1982). From ace to zombie: Some explorations in the language of
personality. In C. D. Spielberger & J. N. Butcher (Eds.), Advances in personality
assessment (Vol. 1, pp. 203–234). Hillsdale, NJ: Erlbaum.
Goldberg, L. R. (1990). An alternative “description of personality”: The Big-Five factor
structure. Journal of Personality and Social Psychology, 59, 1216–1229.
Goldberg, L. R. (1992). The development of markers for the Big-Five factor structure.
Psychological Assessment, 4, 26–42.
Gorsuch, R. L. (1983). Factor analysis. Hillsdale, NJ: Lawrence Erlbaum.
Gough, H. G. (1987). Manual for the California Psychological Inventory. Palo Alto, CA:
Consulting Psychologists Press.
Harman, H. H. (1976). Modern factor analysis. Chicago: University of Chicago Press.
Hathaway, S. R., & McKinley, J. C. (1967). Minnesota Multiphasic Personality Inventory: Manual for administration and scoring. New York: Psychological Corporation.
Jackson, D. N. (1994). Jackson Personality Inventory–Revised manual. Port Huron, MI:
Research Psychologists Press.
Jackson, D. N., Paunonen, S. V., Fraboni, M., & Goffin, R. G. (1996). A five-factor versus
a six-factor model of personality structure. Personality and Individual Differences,
20, 33–45.
John, O. P. (1990). The “Big Five” factor taxonomy: Dimensions of personality in the
natural language and in questionnaires. In L. A. Pervin (Ed.), Handbook of personality: Theory and research (pp. 66–100). New York: Springer-Verlag.
McCrae, R. R., Costa, P. T., Jr., & Busch, C. M. (1986). Evaluating the comprehensiveness
in personality systems: The California Q-set and the five factor model. Journal of
Personality, 54, 430–446.
McCrae, R. R., & John, O. P. (1992). An introduction to the five-factor model and its
applications. Journal of Personality, 60, 175–215.
Mershon, B., & Gorsuch, R. L. (1988). Number of factors in the personality sphere: Does
increase in factors increase predictability of real-life criteria? Journal of Personality
and Social Psychology, 55, 675–680.
Mosier, C. I. (1938). A note on Dwyer: The determination of the factor loadings of a
given test. Psychometrika, 3, 297–299.
Noller, P., Law, H., & Comrey, A. L. (1987). Cattell, Comrey, and Eysenck personality
factors compared: More evidence for the five robust factors? Journal of Personality
and Social Psychology, 53, 775–782.
Paunonen, S. V. (1993, August). Sense, nonsense, and the Big Five factors of personality.
Paper presented at the annual meeting of the American Psychological Association,
Toronto, Ontario.
Paunonen, S. V. (1998). Hierarchical organization of personality and prediction of
behavior. Journal of Personality and Social Psychology, 74, 538–556.
Beyond the Big Five
835
Paunonen, S. V., & Ashton, M. C. (2000). Big-five predictors of academic achievement.
Manuscript submitted for publication.
Paunonen, S. V., & Jackson, D. N. (1996). The Jackson Personality Inventory and the
Five-Factor Model of personality. Journal of Research in Personality, 30, 42–59.
Paunonen, S. V., Rothstein, M. G., & Jackson, D. N. (1999). Narrow reasoning about the
use of broad personality measures in personnel selection. Journal of Organizational
Behavior, 20, 389–405.
Peabody, D. (1987). Selecting representative trait adjectives. Journal of Personality and
Social Psychology, 52, 59–71.
Rothstein, M. G., Paunonen, S. V., Rush, J. C., & King, G. A. (1994). Personality and
cognitive ability predictors of performance in graduate business school. Journal of
Educational Psychology, 86, 516–530.
Saucier, G., & Goldberg, L. R. (1996). Evidence for the Big Five in analyses of familiar
English personality adjectives. European Journal of Personality, 10, 61–77.
Saucier, G., & Goldberg, L. R. (1998). What is beyond the Big Five? Journal of
Personality, 66, 495–524.
Zuckerman, M., Kuhlman, D. M., Joireman, J., Teta, P., & Kraft, M. (1993). A comparison
of three structural models for personality: the Big Three, the Big Five, and the
Alternative Five. Journal of Personality and Social Psychology, 65, 757–768.
Zwick, W. R., & Velicer, W. F. (1982). Factors influencing four rules for determining the
number of components to retain. Multivariate Behavioral Research, 17, 253–269.