Part V: creating the EQ-i 2.0 and EQ 360 2.0
UK and Ireland Norms
EQ 360 2.0 UK and Ireland Standardisation
Standardisation
NORMATIVE SAMPLE
Collection of data for the UK and Ireland EQ 360 2.0 took place in October and November of 2011. Respondents (“the raters”) were required to rate an individual (“the ratee”) on the EQ 360 2.0 and provide demographic information about both themselves and the ratees. In order to create a representative normative sample, specific demographics regarding the ratees, guided by recent UK and Ireland Census information, were considered during the data collection procedures. Information was collected on each ratee’s gender, age group, race/ethnicity, employment status, and geographic region. For the EQ 360 2.0, this information about the ratee (i.e., the person being rated) was provided by the rater (i.e., the person completing the assessment). Information about the type (i.e., manager, work peer, direct report, or family/friend) and strength of the rater-ratee relationship was also collected (i.e., how long have they known each other, how well they know each other, and how often do they interact with each other).
Rater Description: The sample of 1,920 raters (i.e., the participants providing the ratings) was 58.5% male with a mean age of 46.1 years (SD = 13.0 years). The rater sample was primarily White (91.4%), and also included those that were Indian (2.2%), Black (1.9%), and of other races/ethnicities (4.5%). With regard to geographic region, the majority of the raters were from the UK (92.3%), and the remaining raters were from Ireland (7.7%). More than half of the raters (62.7%) had a university degree or equivalent/higher qualifications, many had some university or equivalent (20.8%), and the remaining raters had secondary school/GCSE grades A-C or less (16.6%). The majority of raters knew the ratee for longer than one year (see Table C.23), and more than half stated that they knew the ratee well or very well (57.7%; see Table C.24). More than half (59.4%) of the raters indicated that they interacted with the ratee very often (daily or almost daily; see Table C.25).
Ratee Sample: The normative sample was stratified to match the Census as closely as possible based on the ratees’ demographic characteristics. Table C.26 shows the ratee age group by gender distribution. The ratee sample included an equal ratio of males to females, stratified across four rater types: direct report (i.e., the ratee is the rater’s manager), manager (i.e., the ratee is the rater’s direct report), work peer, and friend/family member (see Table C.27). Race/ethnicity information for the ratee sample is presented in Table C.28 for each country. The majority of the normative sample was White, matching closely to Census proportions. The non-White group was composed of individuals described by the raters as mixed, Indian, Black, or other. Representation by geographic region is shown in Table C.29, with weighted percentages meeting Census targets for both countries within 1%.
NORMING PROCEDURES
Similar to the EQ-i 2.0, the first step in the EQ 360 2.0 norming procedure was to determine if any demographic trends existed in the UK and Ireland normative data. Large differences in scores between rater types (i.e., managers, work peers, direct reports, friends/family members) would suggest a need to create an option for separate rater-type norm groups, while a lack of such differences would suggest a need to create a single norm option with the rater-types combined. Similarly, large differences in scores between male and female ratees, or across various ratee age groups, would suggest a need to create an option for separate gender- or age-based norm groups. Conversely, a lack of such differences may dictate the use of a single norm group with genders and age groups combined. A series of analyses of covariance (ANCOVA; for the Total EI score) and multivariate analyses of covariance (MANCOVA; for the composites and subscales) were used to examine the relationships between rater-type, ratee gender, and age with EQ 360 2.0 scores. Ratee race/ethnicity (White vs. non-White) was included as a covariate in all analyses. In an attempt to control for Type I errors that might occur with multiple analyses, a more conservative criterion of p < .01 was used for all F-tests. Results at the multivariate level revealed significant effects of gender, age, and rater type for the composites and the subscales (see Table C.30). Interaction effects at the multivariate level were not significant. Given these results, the univariate effects are described in detail next.
Gender and age effects. Overall (and similar to what was seen with the North American EQ 360 2.0 data), gender and age effects were less pronounced in the EQ 360 2.0 normative sample than they were in the EQ-i 2.0 normative sample (see Table C.31 for effect sizes and Table C.32 and Table C.33 for descriptive statistics and significance test results).
None of the composites or the Total EI score reached even a small effect size for gender. At the subscale level, three subscales showed small effects (Emotional Self-Awareness, Emotional Expression, and Empathy), with females scoring higher than males.
With respect to age, only three scales reached a small effect size. For Independence, the effect was attributable to lower scores for the 18–29 year-old group, compared to all other age groups. For Flexibility, the 60+ group scored lower than the other groups. For Happiness, the youngest group scored higher than the other groups.
Rater type effects. No differences were observed across rater types for the Total EI score. At the composite and subscale level a number of scales showed differences between rater types, but these were mostly very small effects. For scales reaching at least a small effect size, direct reports provided the highest ratings compared to other rater groups on the Self-Expression composite and the Self-Regard, Assertiveness, Independence, and Problem Solving subscales, and provided the lowest ratings compared to other rater groups on the Interpersonal composite and the Interpersonal Relationships and Empathy subscales. See Table C.31 for effect sizes and Table C.34 for descriptive statistics and significance test results.
Interaction effects. None of the age × gender, age × rater type, or gender × rater type interactions reached even a small effect size at the univariate level.
Norm Groups and Norm Construction. Overall, the d and partial η2 values found in the normative data suggest negligible or very small effects of ratee gender, ratee age, and rater type. The scarcity of meaningful effects suggested that it was not necessary to create specific gender-, age-, or rater type-based norms for the UK EQ 360 2.0, and therefore only Overall norms were developed. These norms were created using the same procedure as the EQ-i 2.0 norms. Standard scores for all scales were computed with a mean of 100 and standard deviation of 15. Results revealed that skewness and kurtosis values were close to 0 (skewness values ranged from -0.78 to 0.05; kurtosis values ranged from -0.34 to 0.27), and an examination of the scale histograms did not reveal any significant departures from a bell-shaped curve. A histogram for the EQ 360 2.0 Total EI score is provided in Figure C.4. The other composite scales and subscales show comparable distributions. Therefore, artificial transformation of scores to fit normal distributions was deemed unnecessary.
Comparison of UK and Ireland Norms to North American Norms. The UK and Ireland sample was compared against the North American normative sample by computing standard scores for the EQ 360 2.0 scales with the North American EQ 360 2.0 norms, and comparing these scores against a mean of 100 (see Table C.35). Although for most scales the effects did reach statistical significance due to the large sample size, most differences were within 3 standard score points, and only three scales (Self-Perception composite, Self-Actualisation, and Emotional Expression) reached a meaningful effect size; for all other scales Cohen’s d values were below 0.20. The only scale on which the UK sample scored significantly higher than the North American sample was Assertiveness, but the effect size was negligible (d = 0.07).
Internal Consistency
Internal consistency conveys the degree to which a set of items are associated with one another. High levels of internal consistency suggest that the items are measuring a single, cohesive construct. Internal consistency is typically measured using Cronbach’s alpha (Cronbach, 1951), which ranges from 0.0 to 1.0 with higher values reflecting higher internal consistency.
Cronbach’s alpha values for the UK EQ 360 2.0 normative sample are displayed in Table C.36. Similar to results found with the North American EQ 360 2.0 data, most values ranged from good to excellent (.82 to .98) across the Total EI, composite, and subscale scores, with only Assertiveness reaching a lower, but still acceptable, level (.78).
Factorial Validity
EXPLORATORY FACTOR ANALYSIS
Exploratory factor analysis (EFA) was used to determine whether the subscales established with the North American EQ 360 2.0 normative data empirically emerge from the UK and Ireland normative dataset. Five EFAs were conducted, analysing the items within each composite scale separately. In each EFA, a three-factor solution was forced to examine whether the items corresponding to each subscale within the composite also loaded together in the UK and Ireland normative data. Principal axis factoring extraction was used, with direct oblimin (i.e., oblique) rotation, as the factors within each composite are expected to correlate with each other. Reverse scoring was applied to relevant items prior to the analysis. Factor loadings were considered significant if they reached at least ± .30, and an item was defined as cross-loading if it was significant on more than one factor and had loadings within .10 of each other on these factors.
For each of the Self-Perception, Self-Expression, and Decision Making Composite EFAs, items for the three subscales loaded together as expected by the established factor structure. All items loaded significantly onto their respective factors, with no cross-loadings. For the Interpersonal Composite EFA, four items either fell below the factor loading cutoff of ± .30 for their respective factor or cross-loaded with another factor. For the Stress Management Composite EFA, all items loaded significantly onto their respective factors with the exception of two items that were cross-loaded.
To summarise, the EFAs generated solutions that strongly correspond to the established EQ 360 2.0 factor structure, with the items for each subscale empirically grouping together onto the expected factors. Of the 126 items included in the EFAs, only six items were either cross-loading or fell below the cutoff of .30.
CORRELATIONS AMONG EQ 360 2.0 COMPOSITE SCALES AND SUBSCALES
Correlations among the EQ 360 2.0 composite scales and subscales were examined in the UK and Ireland normative sample to determine if the pattern of results found in the UK EQ-i 2.0 normative data could be replicated. Table C.37 (composite scales) and Table C.38 (subscales) display these correlations. Overall, these correlations were stronger in the EQ 360 2.0 data. Composite scale correlations ranged from r = .59 (Self-Expression/Interpersonal) to r = .83 (Decision Making/Stress Management). For the subscales, the correlations ranged from r = .25 (Emotional Expression/Independence) to r = .79 (Interpersonal Relationships/Empathy).