Establishing Measurement Invariance of the Cognitive Assessment System Across Cultures

C H A P T E R

8 Establishing Measurement Invariance of the Cognitive Assessment System Across Cultures Ciping Deng1 and George K. Georgiou2 1

School of Psychology and Cognitive Science, East China Normal University, Shanghai, China 2Department of Educational Psychology, University of Alberta, Edmonton, Canada

The quest to develop culture-free and valid tests of intelligence is not new (Rhodes, Ochoa, & Ortiz, 2005; Sternberg & Kaufman, 2011), but has become even more pressing recently due to the flourishing of cross-cultural research and the multicultural nature of our society. Adapting intelligence tests to different languages and cultures has proven to be challenging particularly because of the verbal and quantitative demands of these tests. Although researchers acknowledge that the use of nonverbal IQ tasks has helped them minimize this problem (e.g., Bracken & Naglieri, 2003; McCallum & Bracken, 2012), they also concur that these tests have limitations in regards to instructional planning. Moreover, the use of nonverbal IQ tests has led to findings that are difficult to interpret from an educational perspective (i.e., the East Asian children have superior IQ than their North American counterparts and that alone is sufficient to explain their higher performance in math and science; see Lynn, 2010), which, in turn, has sparked heated debates around the validity of nonverbal IQ tests across cultures (e.g., Brouwers, Van de Vijver, & Van Hemert, 2009; Lynn & Meisenberg, 2010; Rindermann, 2007). Some researchers have argued that intelligence could instead be conceptualized on the basis of neuropsychological processes (e.g., Das, 2002;

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Das, Kirby, & Jarman, 1979; Naglieri & Otero, 2011). This has an important advantage over traditional IQ tests because processing tests avoid school-based content questions, thus making the tests more appropriate for assessment of culturally and linguistically diverse populations. In this study, we examined the measurement invariance in Canadian and Chinese grade 1 students of one such test, the Das-Naglieri Cognitive Assessment System (D-N CAS; Naglieri & Das, 1997), that is based on the Planning, Attention, Successive, and Simultaneous (PASS) processing theory of intelligence (e.g., Das, Naglieri, & Kirby, 1994). Our chapter begins with a brief overview of the PASS theory and of the crosscultural studies that have used it. The PASS theory of intelligence proposes that cognition is organized into three systems and four processes (Das et al., 1994). The first system is Planning, which involves executive functions responsible for controlling and organizing behavior, selecting and constructing strategies, and monitoring performance. The second is Attention, which is responsible for maintaining arousal levels and alertness, and ensuring focus on relevant stimuli. The third is an Information Processing system; it employs Simultaneous and Successive processing to encode, transform, and retain information. Simultaneous processing is engaged when the relationship between items and their integration into whole units of information is required, as in analysis and synthesis of logical-grammatical relationships both in verbal and nonverbal problems. Successive processing is required for organizing separate items in a sequence as, for example, remembering a sequence of words or actions exactly in the order in which they had just been presented. The four processes have been assessed with the D-N CAS (Naglieri & Das, 1997), which includes 12 tests (3 tests for each PASS process). These tests have provided useful information in relation to educational/ clinical problems in typical and atypical populations (e.g., learning disabilities and attention deficit; see Deng, Liu, Wei, Chan, & Das, 2011; Huang, Bardos, & D’Amato, 2010; Papadopoulos, Constantinidou, & Douklias, 2010), cognitive changes in aging (Das et al., 1994), and decision making (Das, Kar, & Parrila, 1996). To date, many studies have examined the relationship between D-N CAS, academic achievement, and other intelligence tests (e.g., Das, Georgiou, & Janzen, 2008; Naglieri, DeLauder, Goldstein, & Schwebech, 2006; Naglieri & Rojahn, 2004; Papadopoulos, 2001). For example, Naglieri et al. (2006) found that the D-N CAS correlated more strongly with academic achievement than WISC-III (i.e., corrected correlations between D-N CAS and WJ-III ranged from .49 to .88 with a median of .69, whereas corrected correlations between WISC-III and WJ-III ranged from .32 to .81 with a median of .62), and that it also predicted academic achievement more effectively than WISC-III.

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The majority of studies with D-N CAS have been conducted in North America (see Das, 2002, for a review). However, D-N CAS has been adapted and used in many other languages, such as Greek (e.g., Papadopoulos, 2013; Papadopoulos, Georgiou, Kendeou, & Spanoudis, 2008), Dutch (e.g., Van Luit & Kroesbergen, 1998), Spanish (e.g., Iglesias-Sarmiento & Dean˜o, 2011; Naglieri, Otero, DeLauder, & Matto, 2007), Italian (e.g., D’Amico, Cardaci, Di Nuovo, & Naglieri, 2012; Taddei & Naglieri, 2005), Korean (Naglieri & Das, 2006), Japanese (e.g., Maekawa, Nakayama, & Okazaki, 2007), and Chinese (e.g., Cai, Li, & Deng, 2013; Deng et al., 2011). With few exceptions (e.g., Kranzler & Keith, 1999), the construct validity of the D-N CAS model has been empirically confirmed (Deng et al., 2011; Naglieri, Das, Stevens, & Ledbetter, 1991; Papadopoulos, 2001). The researchers that have used D-N CAS in other languages/cultures have been working under the assumption that D-N CAS functions the same way in their own language/culture as it does in English. This assumption has been reinforced by recent evidence showing that children in other languages/cultures have similar subscale scores as American children (when U.S. norms are used to score their performance; see Kroesbergen, Van Luit, Naglieri, Taddei, & Franchi, 2010; Naglieri, Taddei, & Williams, 2013) and that the cognitive profiles of bilingual children are similar in both the English and Spanish versions of the D-N CAS (Naglieri et al., 2007). To our knowledge, only one study has directly tested the factor structure of D-N CAS across cultures. Specifically, Naglieri et al. (2013) examined the measurement invariance of D-N CAS in a study with 809 Italian and 1,174 American children. Similar to previous cross-cultural studies (e.g., Kroesbergen et al., 2010), the U.S. norms were used to calculate standard scores in each sample (a practice that is problematic for several reasons). The results of multigroup analyses confirmed the measurement invariance of the D-N CAS factor structure for both the 5- to 7-year-old and the 8- to 18-year-old age groups. In addition, Naglieri et al. found that despite the small mean score differences between the performance of the U.S. and Italian children on the PASS constructs, the Full Scale score in the two groups was almost identical (100.9 for the Italian and 100.5 for the American). On the basis of these findings, Naglieri et al. (2013) concluded that “the CAS subtests measure the PASS neurocognitive abilities similarly between groups” (p. 164). As an assessment system, the D-N CAS has a fair chance of both exposing cultural nuances and explaining them. D-N CAS has two conditions that perhaps are conducive to a comparison of mental functions across cultures: (a) it does not have test items that overlap with school-learned content to the same extent as traditional tests of IQ, and

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(b) it is based on a theoretical model comprising basic cognitive processes that are the foundations of intelligence. These processes are likely to be universal as they have a basis in the functional organization of the brain. However, all intellectual functions or higher mental activities have their origin in the culture in which an individual functions (Luria, 1979); cultural differences are therefore anticipated (see Das, Mehta, Nakayama, & Janzen, 2013, for some preliminary evidence). D-N CAS is thus suitable for investigating both the commonality and the differences between different cultural groups, thereby recognizing socialhistorical origins of cognitive differences. The existing cross-cultural studies on D-N CAS have all been conducted in Western societies that have similar curricula, instructional practices, and school settings. In this study, we compare the factor structure of D-N CAS in two cultural groups (Canadian and Chinese) that are known to diverge in many respects (see Feng, Miller, Shu, & Zhang, 2009, for a discussion of orthographic differences between English and Chinese; and Ng, Pomerantz, & Lam, 2007, for a discussion of cultural differences between East Asian and American children in relation to performance). Importantly, the selected cultures represent different modes of thinking. Drawing on the distinction between “holistic” and “analytic” thinking, cultural psychologists have argued that these two modes of thinking are unevenly distributed across cultures; the former is more prevalent in East Asian cultures and the latter in Western cultures (Nisbett, 2003; Norenzayan, Choi, & Peng, 2007). Whereas East Asians tend to rely more on context to make decisions, North Americans tend to decontextualize, using feature-based and rule-based strategies (Nisbett, Peng, Choi, & Norenzayan, 2001). Given that one of the functional units in PASS theory involves how we process information (simultaneous or successive processing), examining D-N CAS across two cultures that favor different ways of processing information is important.

METHOD Participants One-hundred-twenty Grade 1 English-speaking Canadian children from Edmonton (65 girls and 55 boys, mean age 5 81.73 months, SD 5 5.16) and 181 Grade 1 Mandarin-speaking Chinese children from Shanghai (82 girls and 99 boys, mean age 85.85 months, SD 5 3.53), whose parents gave consent for them to participate in the

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study, were assessed. They were all native speakers of English and Mandarin, respectively. The children in both countries came mostly from middle-to-upper-middle SES families. Not one of the children participating in this study was identified as having learning, emotional, or sensory disabilities.

Materials PASS processes. The PASS processes were assessed with the DasNaglieri Cognitive Assessment System (D-N CAS; Naglieri & Das, 1997). For the purpose of this study, we administered only the basic CAS battery, which included two measures per subscale. Naglieri and Das (1997) reported good psychometric properties for the CAS subscales with average internal consistency values as follows: Planning 5 .85, Simultaneous 5 .90, Attention 5 .84, and Successive 5 .90. Planning was assessed with two measures: Matching Numbers and Planned Connections. In Matching Numbers, the participants were presented with four pages containing eight rows of numbers that were increasing in size. For each row, the participants were instructed to underline the two numbers that were the same. The time and number correct for each page were recorded, and the subtest score was calculated by combining both time and number correct. The Planned Connections task required the subject to develop some effective way of connecting sequential stimuli (numbers from 1 to 25), which were quasi-randomly distributed on a page. In this study, the task consisted of five items. The participants’ score was the combined time to complete items 1 to 5. Attention was assessed with two measures: Expressive Attention and Receptive Attention. In Expressive Attention, all children were given three pages of stimuli to name. The children were shown animals that were either “small” (a butterfly, a mouse, a bird, and a frog) or “big” (an elephant, a whale, a horse, and a dinosaur) and were asked to name them as fast as possible by referring to their actual size. In the neutral condition, all of the pictures were of the same physical size; in the congruent condition, the size of the pictures was in line with the actual size of the animals; and in the incongruent condition, the pictures of the animals were most of the times in contrast to their actual size. For each condition, the children named stimuli from a practice card prior to the experimental trial. The response time to name each card and the number of errors were noted. In the Receptive Attention subtest, the participants were given four sheets consisting of 50 picture pairs each. In the first two items, the participants’ task was to underline only those pairs of pictures that were visually alike (picture matching). In the last two items, the participants were instructed to underline those pairs that

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belonged to the same taxonomic category (name matching). The participants were allowed 180 seconds to complete the task. The participants’ score was a ratio of accuracy (total number correct minus the number of false detections) to total time taken to complete all items. Simultaneous processing was assessed with two measures: Nonverbal Matrices and Verbal Spatial Relations. In Nonverbal Matrices, the children were presented with a pattern of shapes/geometric designs that was missing a piece and were asked to choose among six alternatives the piece that would accurately complete the pattern. A discontinuation rule of four consecutive mistakes was applied. The participants’ score was the total number correct. In Verbal Spatial Relations, the children were presented with six drawings, arranged in a specific spatial manner, and a printed question. They were then instructed to choose one of the six drawings that best answers the question within a 30-second time limit. A discontinuation rule of four consecutive mistakes was applied. The participants’ score was the total number correct. Finally, Successive processing was assessed with Word Series and Speech Rate. In Word Series, the examiner read a series of words, varying in length from four to nine words, and then asked the participants to repeat the words in the same order. This task uses the following nine single-syllable, high-frequency words: “Book,” “Car,” “Cow,” “Dog,” “Girl,” “Key,” “Man,” “Shoe,” and “Wall.” A discontinuation rule of four consecutive mistakes was applied. The participants’ score was the total number of word series correctly repeated. In Speech Rate, the participants were required to say aloud three familiar and phonetically dissimilar words (e.g., “Man,” “Cow,” “Key”) as fast as possible 10 times. The task consisted of eight three-word series, and the participants’ score was the combined time to complete all eight items.

Procedures All tests were individually administered by a group of graduate students that received training prior to testing. Testing was completed in one session that took place in a quiet room in the school. Testing lasted approximately 40 minutes, and the tasks were administered in fixed order.

Data Scoring The scoring of the PASS processes was completed following the instructions in the manual (Naglieri & Das, 1997). However, because there are no norms for Chinese children, and because we wanted to use the same metric across cultures, we converted the raw scores in each task to z scores and used the z scores in the analyses. In addition, we

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RESULTS

multiplied the z scores in Planned Connections and Speech Rate by to keep the direction of the scores across all tasks the same.

1

RESULTS Measurement Invariance of D-N CAS Across Cultures To examine if the measurement model of D-N CAS was similar across the two cultures, we first ran confirmatory factor analysis (CFA) in AMOS v20 for each culture separately. Maximum likelihood estimation procedures were used to analyze the variance/covariance matrix. To evaluate the model fit, chi-square values and a set of fit indexes were used: (a) the Comparative Fit Index (CFI); (b) the Incremental Fit Index (IFI); and (c) the Root Mean Square Error of Approximation (RMSEA). The results (see Figures 8.1 and 8.2) indicated that the model fitted the data very well in each culture [Canadian: χ2 (14) 5 19.77, .49 er1

Planned Connections

er2

Matching Numbers

er3

Expressive Attention

.70

PLANNING

.47 .68

.88

.41 .64

er4

Receptive Attention

.68

ATTENTION

.35 .59

.25 er5

Nonverbal Matrices

er6

Verbal-Spatial Relations

.50

SIMULTANEOUS

.59

.60 .77

.32 er7

Word Series

.37 .57

.33 er8

Speech Rate

.60

.54

SUCCESSIVE .57

FIGURE 8.1 The structure model of D-N CAS in the Canadian sample.

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8. MEASUREMENT INVARIANCE OF THE COGNITIVE ASSESSMENT SYSTEM .48 er1

Planned Connections

.69

PLANNING

.40 er2

Matching Numbers

er3

Expressive Attention

.64 .88

.31 .56

er4

Receptive Attention

.49

ATTENTION

.63 .79

.18 er5

Nonverbal Matrices

er6

Verbal-Spatial Relations

.42

SIMULTANEOUS

.27

.63 .52

.18 er7

Word Series

.45 .42

.59 er8

Speech Rate

.54

.64

SUCCESSIVE .77

FIGURE 8.2 The structure model of D-N CAS in the Chinese sample.

p 5 .137, CFI 5 .963, IFI 5 .966, RMSEA 5 .059; Chinese: χ2 (14) 5 20.27, p 5 .122, CFI 5 .973, IFI 5 .974, RMSEA 5 .050]. After examining the factor structure of D-N CAS in each culture separately, we examined measurement invariance across cultures by performing multigroup analyses. The analysis was performed in two steps: first, we tested the fit of a multigroup model in which no cross-cultural constraints (i.e., factor loadings, variances, and covariances being equal across cultures) were imposed. This was followed by testing the invariance of the factor loadings across cultures. In testing for the invariance of the factor loadings, we compared the χ2 value of the constrained model (factor loadings being equal across cultures) with that of the initial multigroup model in which no cross-cultural constraints were imposed. Next, we compared the initial unconstrained model to a model in which both factor loadings and variances were constrained to be equal across cultures. Finally, we compared the initial unconstrained model to a model in which all factor loadings, variances, and covariances were constrained to be equal across cultures. Table 8.1 presents

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TABLE 8.1

Results of Multigroup Analyses

Model

df

x2

Δdf

Δx2

p value

1.

No equality constraints imposed

28

40.06

2.

Factor loading equal across cultures

32

45.74

4

5.68

.224

3.

Factor loadings and variances equal across cultures

36

48.36

8

8.30

.405

4.

Factor loadings, variances, and covariances equal across cultures

42

55.19

14

15.13

.369

the results of this analysis. Importantly, none of the model comparisons reached significance.

DISCUSSION The objective of this study was to examine whether the proposed factor structure of D-N CAS was similar in Canada and China. Our findings suggest that D-N CAS is cross-culturally valid. Despite some small differences in the values of the factor loadings and the covariances between the factors, the model comparisons across the two cultures were not significant. These findings are similar to those by Naglieri et al. (2013), in which the measurement invariance of D-N CAS was examined in a large group of Italian and American children. They further reinforce the argument put forward by some researchers that a theory of intelligence based on assessment of neuropsychological processes may have advantages over traditional IQ tests and be more suitable for use in culturally diverse populations (Das, 2002; Naglieri & Otero, 2011). We demonstrated that this is true even when we engage two cultures with different modes of thinking (the Chinese being more holistic and the Canadian being more analytic). Future studies should examine the possible effect of PASS processes on academic achievement across cultures. Although Kroesbergen et al.’s (2010) cross-cultural study on the effect of PASS processes on mathematics in Italian and Dutch children moves toward this direction, no firm conclusions can be drawn from that study because of the small sample sizes. Given that culture interacts with intelligence (Sternberg, 2004) and could foster a specific kind of cognitive processing (Nisbett et al., 2001), significant differences in the role of PASS on academic

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achievement across cultures are anticipated. Freeing ourselves from the dominant practice of calculating standard scores in other cultures based on U.S. norms (which were developed in 1997) may be a necessary first step in unraveling which cognitive processes are universal and which are culturally specific. For those conducting cross-cultural research, D-N CAS provides a reliable option to assess cognitive processes and intelligence. As such, D-N CAS would have no problem explaining the observed superiority of East Asian children in nonverbal IQ (Lynn, 2010). It reflects their superiority in simultaneous processing, which is a hallmark of “holistic” mode of thinking. In contrast, Westerners demonstrate superiority in successive processing, which is an index of “analytic” mode of thinking. Nonverbal IQ tests such as Raven’s Progressive Matrices favor only one mode of thinking. Despite the fact that it takes relatively long to administer, the discriminatory and predictive power of D-N CAS (see Huang et al., 2010; Papadopoulos et al., 2010) coupled with its sensitivity to cultural idiosyncrasies allow us to see its future with optimism.

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