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Factor Structure of the Korean Version of Wong and Law's Emotional Intelligence Scale
Eriko Fukuda, Donald H. Saklofske, Katsuo Tamaoka and Hyunjung Lim
Assessment 2012 19: 3 originally published online 6 December 2011
DOI: 10.1177/1073191111428863
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91111428863Fukuda et al.Assessment© The Author(s) 2012

ASM19110.1177/10731

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Factor Structure of the Korean
Version of Wong and Law’s
Emotional Intelligence Scale

Assessment
19(1) 3­–7
© The Author(s) 2012
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DOI: 10.1177/1073191111428863
http://asm.sagepub.com

Eriko Fukuda1, Donald H. Saklofske2, Katsuo Tamaoka3, and Hyunjung Lim4

Abstract
This study reports the factor structure of a Korean version of the 16-item Wong and Law Emotional Intelligence Scale(WLEIS) for a sample of 161 Korean university students. Confirmatory factor analysis supported the four-factor model ofthe WLEIS: (1) self-emotional appraisal, (2) others’ emotional appraisal, (3) use of emotion, and (4) regulation of emotion.
However, improvement of the model fit after removing three items suggests the need for future research on the crosscultural measurement invariance of the WLEIS.
Keywords
emotional intelligence, factor analysis, validity, university students, Korean

Introduction
Two theoretical models of emotional intelligence (EI)
dominate the current research literature. Ability EI is anintelligence, defined as “the ability to perceive and express
emotion, assimilate emotion in thought, understand andreason with emotion, and regulate emotion in the self andothers” (Mayer & Salovey, 1997, p. 5). Trait EI is a “constellation of emotional self-perceptions located at the lower
levels of personality hierarchies” (Petrides, 2010, p. 137).
Research supports the relationship between trait EI andpositive life experiences, including life satisfaction, academic
success (Austin, Saklofske, & Mastoras, 2010; Schutte
et al., 2010), and both mental and physical health (Austin,
Saklofske, & Egan, 2005; Keefer, Parker, & Saklofske,
2009; Parker, Taylor, & Bagby, 2001).
Cross-cultural studies of ability EI are challenging
because judging correct responses is difficult and cultural
display rules vary among ethnic groups resulting in East–
West response differences. Alternatively, self-report tests
require respondents to rate their typical behaviours on a
Likert-type scale and consequently, assessing trait EI
appears less difficult than performance testing. However,cross-cultural EI assessment raises the key issue of measurement invariance. The Schutte Emotional Intelligence
Scale (SEIS; Schutte et al., 1998) shows different factorial
structures even within Western cultures (Austin, Saklofske,
Huang, & McKenney, 2004).
Differences in emotional expression across culturalgroups (Matsumoto, 1993; Matsumoto & Ekman, 1989)

may be a key issue when examining the factorial invariance
in EI measures. Chan (2004) found the SEIS contained many
uninterpretable items for teachers from Hong Kong; only 12
items remained from the original 33 items. Poor functioning
items might be culturally biased, reflecting differences
between Western and Chinese cultures in the meaning andreporting of emotional behaviors and experiences.
The Wong and Law Emotional Intelligence Scale(WLEIS; Wong & Law, 2002), developed in Hong Kong,
has been examined in cross-cultural studies. The 16-item
self-report WLEIS, based on the Mayer and Salovey (1997)
EI model, measures four dimensions: Self emotional
appraisal (SEA) measures the individual’s ability to understand their emotions, others’ emotional appraisal (OEA) isthe ability to recognize and understand other people’s emotions, use of emotion (UOE) is the tendency to motivate
oneself to enhance performance, and regulation of emotion(ROE) assesses the ability to regulate emotions.
The WLEIS was cross-validated with several East Asiangroups from China (Law, Wong, & Song, 2004; Shi &1

University of Calgary, Alberta, Canada
University of Western Ontario, London, Ontario, Canada
3
Graduate School of Languages and Cultures, Nagoya University, Nagoya, Japan
4
Yamaguchi Prefectural University, Yamaguchi, Japan
2

Corresponding Author:
Eriko Fukuda, EDT #940, Division of Applied Psychology, Faculty of
Education, University of Calgary, 2500 University Drive, N.W., Calgary,Alberta, Canada, T2N 1N4
Email: efukuda@ucalgary.ca

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Assessment 19(1)Wang, 2007; Wong & Law, 2002) and Japan (Fukuda et al.,2011) supporting the four-dimensional structure (Fukuda
et al., 2011; Law et al., 2004; Shi & Wang, 2007), the predictive validity with life satisfaction (Fukuda et al., 2011;
Law et al., 2004), and discriminant validity with the fivefactor personality dimensions (Law et al., 2004; Shi &Wang, 2007; Wong & Law, 2002). The WLEIS is a promising cross-cultural EI measure. The purpose of the present
study was to further examine the factorial structure of the
WLEIS with Korean university students.

MethodParticipants
Korean university students whose first language is Korean
were recruited from universities in and outside Seoul,
South Korea. A sample included 161 students, 78 males
and 83 females (M = 20.75 years, SD = 2.04).

MeasureThe WLEIS (Japanese version) was translated into Korean
by a bilingual native Korean researcher, and blindly backtranslated by another bilingual native Korean researcher toensure language equivalence. Japanese and Korean are linguistically similar and consequently, one round of backtranslation was required as language equivalence is relatively
easily achieved. The translated WLEIS retained the original
16 items and the 7-point Likert-type response format.

Procedure
The current research was part of a larger study following
ethical procedures established in Korean universities.
Information about the study was given to students in theirclasses, and those who volunteered to participate received apen. Participants completed the WLEIS in group testing
sessions of about 10 minutes.

Analysis
Missing values, comprising less than 1% of data, were
imputed by a stochastic regression imputation method using
the LISREL 8.80 (Jöreskog & Sörbom, 2006). Confirmatory
factor analysis was conducted using LISREL 8.80 and thefollowing four measures of fit were used to evaluate themodel adequacy: chi-square, nonnormed fit index (NNFI;
Bentler & Bonett, 1980), comparative fit index (CFI;
Bentler, 1990), and root mean square error of approximation(RMSEA; Steiger, 1990). Values ≥.90 show acceptable fit
for the NNFI and the CFI, and values ≤.08 are acceptable for
the RMSEA (Kline, 2005).

Table 1. Descriptive Statistics, Correlations, and Reliabilities
Among the Four WLEIS Subscales
Subscales

M

SD

SEA

OEA UOE Internal consistency

SEA
OEA
UOE
ROE

5.09
5.02
5.07
4.53

1.07 —
0.97 .46** —1.01 .45** .26** —1.10 .12.24** .23**

.80
.74
.74
.83

Note. WLEIS = Wong and Law Emotional Intelligence Scale; SEA = SelfEmotion Appraisal; OEA = Other’s Emotion Appraisal; UOE = Use of
Emotion; ROE = Regulation of Emotion. N = 161.
Pearson correlation coefficients. **p < .01 (two-tailed tests).

Results
Descriptive Statistics, Correlations
Among the Four Subscales, andInternal Consistency Reliability
Means and standard deviations of the subscales, the correlations between the subscales, and reliability are reported inTable 1. Except between SEA and ROE, the correlations
were statistically significant. Reliabilities for all domains
and the total WLEIS were satisfactory following Nunnallyand Bernstein’s (1994) recommendation of .70 or higher
for acceptable reliability.

Factor Analysis
Two models tested the fit to the observed data. The fullmodel consists of the four correlated factors; each comprised of four items. The second model (restricted model)
was a second-order factor model consisting of a general EI
factor and the four aforementioned first-order factors. The
second-order factor model has been supported in otherstudies (Fukuda et al., 2011; Kafetsios & Zampetakis,
2008; Law et al., 2004; Whitman, Van Rooy, Viswesvaran,& Kraus, 2009; Wong & Law, 2002). Both models tested
are congeneric models (Lee, Dunbar, & Frisbie, 2001),
which consist of free lambda loadings and a diagonal thetamatrix that estimates residual variances; no residual covariances were fit to the data.
The indices for the both models indicated a good fit tothe observed data (Table 2). The results of the chi-squaredifference test was significant, Δχ2(2) = 6.344, p = .042;
thus the full model best described the observed data. Factor
loadings and variance explained by the four factors andsquared multiple correlations for each indicator are reported
in Table 3. The factor loadings of the full model are presented in Figure 1. The majority of items show excellent
factor loadings (>.70), three have very good factor loadings(>.63), two show fair factor loadings (>.45), and one item
has a poor factor loading (>.32; Comrey & Lee, 1992). All

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Fukuda et al.
Table 2. Fit Indices for the Full and Restricted Models

Model

NNFI CFI RMSEA

90% CI

Minimum fit
function χ2

LL

χ2

UL

df

Item 1
Item 2p

Item 3−0.079 0.043 155.572 98 <.001−0.079 0.044 161.916 100 <.001

Item 4Note. NNFI = nonnormed fit index; CFI = comparative fit index; RMSEA =root mean square error of approximation; CI, confidence interval; LL,
lower limit; UL, upper limit.

Item 6Full.951 .960
Restricted .948 .957

.062
.062

.709**.806**.849**

SEA.523**.554**

Item 5Item 7.652**.755**.468**.496**

OEA.712**

Item 8

Table 3. First-Order Factor Loadings and Variance Explained
for the Wong and Law Emotional Intelligence Scale

Parameter estimates
Item
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16

Unstandardized
1.110
1.006
1.104
0.660
0.791
1.071
0.639
0.833
0.584
0.883
1.070
0.962
0.820
1.030
1.109
1.049

Standardized
0.709
0.806
0.849
0.523
0.652
0.755
0.468
0.712
0.444
0.633
0.762
0.769
0.631
0.773
0.757
0.796

Squaredmultiplecorrelations
for theindicator
.502
.649
.721
.274
.426
.570
.219
.507
.197
.400
.581
.592
.398
.597
.573
.634

Averagevariance
explained by
the constructs.537.391**

Item 9Item 10Item 11.444**.633**.762**.769**UOE

Item 12.129.325**.245**

Item 13
Item 14
Item 15.631**.773**.757**

ROE.796**

Item 16

.431

.443

.551

factor loadings and correlations between the underlying
factors are statistically significant except for the correlation
between the SEA and the ROE. Correlations among thefour WLEIS dimensions range from small to large thoughmostly in the moderate range (Figure 1).
Since three items—Item 4 (“I always know whether or
not I am happy”), Item 7 (“I am sensitive to the feelings andemotions of others”), and Item 9 (“I always set goals formyself and then try my best to achieve them”), from the fullmodel showed lower factor loadings, a four-factor structure
without these three items (13-item WLEIS), was also examined. The indices for this third model indicated a good fit tothe observed data, NNFI = .958, CFI = .968, RMSEA = .061,
90% CI [−0.083, 0.036]. The Akaike information criterion(AIC) indicates that this model (AIC = 157.944) has a relatively better fit and fewer parameters when compared withthe full model (AIC = 233.316). However, the 16-item

Figure 1. Four-factor confirmatory factor analysis model of the
Wong and Law Emotional Intelligence Scale (full model)
Note. SEA = Self-Emotion Appraisal; OEA = Other’s Emotion Appraisal;
UOE = Use of Emotion; ROE = Regulation of Emotion.
**p < .01

WLEIS was selected as the appropriate model for the following reasons: (1) Confirmatory factor analysis is generally conducted for theory testing instead of theory generating
to ensure a strong theoretical foundation to test the model
fit; (2) the 16-item WLEIS fits well to the observed data;and (3) the three items in question still meet the minimum
requirement of .32 for interpretable data (Comrey & Lee,1992). Removing the three items would potentially require
modifying the original theoretical framework, which would
then need to be applied in future work with a similar sample. The authors did not feel that this was justified in thecurrent context.

Discussion
The Korean version of the WLEIS retained the originalfour-factor structure and added support for the reliability ofthe scale as well as evidence of the generalizability of the
WLEIS in non-Western cultures.
More research is necessary to clarify the inconsistentintercorrelations among the SEA and ROE subscales incontrast to the studies reporting statistically significant correlations among all subscales (Fukuda et al., 2011; Ng,

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Assessment 19(1)Wong, Zalaquett, & Bodenhorn, 2007; Wong & Law,
2002). This may be because of cultural factors in processing
emotions, sampling characteristics, or the subscale and item
composition. Future studies, including mediating variables
such as individualism and collectivism, may elucidate theinconsistent intercorrelations since these cultural orientations can impact emotional perceptions and expressions.
Removing Items 4, 7, and 9 improved the model fit.
Comparing the Japanese results (Fukuda et al., 2011), atleast two of the lower loading items (items 7, 9) seem to be
unique to the Korean sample. Research is required to conclude whether these items truly reflect unique cultural factors or are just less effective items. An item response theory
approach would provide clarification regarding item functioning questions.
Although the sample size was small, 100 to 200 subjects
are considered a “medium” sample size. Furthermore, themodels tested here meet Kline’s (2005) factor structure recommendation that they should be comprised of at least three
indicators per factor; the WLEIS has four indicators per factor. Larger studies are now required to replicate, or challenge
the findings of this study and to examine the convergent anddiscriminant validity of the Korean version of the WLEIS.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect tothe research, authorship, and/or publication of this article.

Funding
The authors received no financial support for the research, authorship, and/or publication of this article.

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