The French Adaptation of the WAIS-III Main Results and Methodological Issues

1. The French Adaptation of the WAIS-IIIMain Results and Methodological Issues Jacques Grégoire Université catholique de Louvain Belgium

2. ITC Guidelines for Adapting Educational and Psychological Tests First publication in 1994 in European Journal of Psychological Assessment, 1. 229-244. 22 guidelines organized into four categories: • Context (C1 & C2), • Instrument development and adaptation (D1 to D10), • Administration (A1 to A6), • Documentation and score interpretation (I1 to I4).

3. Equivalence between the Original and the Adapted Tests Several guidelines are devoted to this issue. Among them: • C.2 The amount of overlap in the constructs in the populations of interest should be assessed. • D.7 Instrument developers/publishers should apply appropriate statistical techniques to (1) establish the equivalence of the different versions of the instrument, and (2) identify problematic components or aspects of the instruments which may be inadequate to one or more of the intended populations.

4. What is at Stake? • Theoretical issue: What is the level of universality of the construct? • Political issue: Are there differences between populations? (e.g. TIMSS, ORCD/PISA…) • Clinical issue:To what extend can the information collected with the original instrument be used to interpret the scores on the adapted instrument?

5. The French Adaptation of the Wechsler Adult Intelligence Scale (WAIS-III) • Much more than a literal translation. • Several new items had to be created for the French version. • The new items had to be equivalent to the original ones, i.e. having the same: (1) format; (2) scoring principles; (3) psychometric characteristics (difficulty, discrimination, validity and reliability). • The final set of items was selected after a field test and a careful analysis of all the collected information.

7. Assessing the Constructs’ Overlapping • The main goal of the item adaptation is measuring the same construct with the adapted version of the test against the original one. • A construct is a model of the phenomenon under interest. • A construct can empirically be checked using the relations between the observed variables. • Factor analysis and Structural Equation Modelling (EM) are the most popular methods for assessing the construct validity of a test and the overlapping of constructs in several populations.

8. Assessing the Constructs Overlapping (continued) • Constructs’ overlapping is a necessary, but insufficient condition of equivalence between an original and an adapted test. • Constructs’ overlapping is required for using the original subscales and subscores in the adapted test. • When an original construct is not found with an adapted test, it means that (1) the original construct is irrelevant in the population for which the test was adapted; or (2) the adapted items used to highlight the construct are irrelevant.

9. Construct Validity of the French WAIS-III • Data of the French standardization sample were used; stratification criteria = age, gender, socio-economic status, and city size. • French sample size = 1,104 (US = 2,450); age range from 16 through 79 (12 age groups). • Data collected by a team of trained psychologists according to the same administration and scoring rules used with the original U.S. WAIS-III. • The reliability coefficients of the French WAIS-III subtests were close to those of the U.S. WAIS-III.

10. Reliability Coefficients

11. Construct Validity of the French WAIS-III (continued) • The construct underlying the WAIS-III is based on the Horn-Cattel’s (1966), the Gustafsson’s (1984) and the Carroll’s (1993) models of intelligence. • The WAIS-III subtests are organized according to four major dimensions of intelligence. Based on these four scales, four Index scores can be computed: Verbal Comprehension, Perceptual Organization, Working Memory, and Processing Speed. • Several factor analyses have provided strong support to the four-factor structure of the U.S. WAIS-III (e.g., Wechsler, 1997; Saklofske et al., 2000; Ward et al., 2000).

12. Exploratory Factor Analysis • Principal axis factoring. • Promax rotation allowing factors to correlate. • According to the scree test and the eigenvalues, four factors were extracted. • The four-factor solution was compared to simpler ones (one factor, two factors and three factors).

13. Promax factor pattern coefficients for the French and U.S. WAIS-III

14. Confirmatory Factor Analysis • Conducted with the LISREL 8.3 program on the total sample and on three age samples (simultaneously), using the variance-covariance matrices. • Four factor models were tested: one-, two-, three- and four-factor models; the last one corresponding to the model underlying the U.S. WAIS-III. • Four fit statistics were considered to compare how well the different models fitted the data : the chi-square, the adjusted goodness-of-fit index (AGFI), the root mean square of approximation (RMSEA), and the comparative fit index (CFI).

15. Goodness-of-Fit Indices for Four CFA Models (N = 1,104)

16. Discussion • Exploratory and confirmatory factor analyses of the French standardization sample supported the four-factor model. • Very similar factor pattern coefficients were observed between the U.S. and the French standardization samples.

17. Discussion (continued) • However, the Arithmetic subtest did show clear alignment with the Working Memory factor, having close coefficients on the Verbal Comprehension and the Working Memory factors . • Similar observation was made with the French adaptation of the WISC-III, and seems related to the larger role of the verbal component in the French Arithmetic items (French is less synthetic than English).

18. Limitations • Byrne & Watkins (2003) emphasized that the replication of factor structure across cultural groups is not sufficient evidence of measurement invariance. • Byrne & Campbell (1999) showed that, despite excellent fit to the data in three different cultures, the same instrument (BDI) was far from equivalent across groups. The saliency of factor loadings, the skewness of item scores, and the pattern of item responses differed across cultures.

19. Levels of Invariance Several levels of invariance (Meredith, 1993; Vandenberg, 2002) • Configural invariance: same number of factors and same pattern of factor loadings across groups. • Metric invariance: configural invariance + same factor loadings across groups. • Scalar invariance: metric invariance + same intercept of item regressions on the latent variables across groups. • Uniqueness invariance: scalar invariance + same item unique variances across groups

20. Testing the Level of Invariance • Vandenberg & Lance (2000) proposed a sequence of 8 tests to assess an instrument’s level of invariance across groups. • Configural invariance is required before testing for metric invariance. • Conducting construct validity studies on the standardization sample of an adapted instrument is a starting point. It is a necessary step, but not a final one.