Factorial invariance of child self-report across race/ethnicity groups: a multigroup confirmatory factor analysis approach utilizing the PedsQL 4.0 Generic Core Scales.
OBJECTIVE
In order to compare health-related quality of life (HRQOL) research findings across race/ethnicity subpopulations, it is important to demonstrate factorial invariance, i.e., that the items have equivalent meaning across the race/ethnicity groups studied. This study examined the factorial invariance of child self-reported HRQOL across race/ethnicity groups for ages 5-18 years utilizing the 23-item PedsQL 4.0 Generic Core Scales.


METHODS
Multigroup confirmatory factor analysis (CFA) was performed, specifying a five-factor model across four race/ethnicity groups (White Non-Hispanic, Hispanic, Asian/Pacific Islander, Black Non-Hispanic). Multigroup structural equation models were proposed in order to compare the factor structure across the four race/ethnicity subpopulations. The analyses were based on 5,490 children recruited from clinic, school, and community populations.


RESULTS
Strict factorial invariance across the four race/ethnicity groups was demonstrated based on stability of the Comparative Fit Index (CFI) between the models, and several additional indices of practical fit including the Root Mean Squared Error of Approximation (RMSEA), the Non-Normed Fit Index (NNFI), and the Parsimony Normed Fit Index (PNFI).


CONCLUSIONS
The findings support an equivalent five-factor structure across the four race/ethnicity subpopulations studied. Based on these data, it can be concluded that children across the four race/ethnicity groups studied interpreted items in a similar manner regardless of their race/ethnicity.
Limbers
Christine A
CA
Department of Psychology, College of Liberal Arts, Texas A&M University, College Station, TX 77843-3137, USA.
Newman
Daniel A
DA
Varni
James W
JW
D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D003625:Data Collection / Q000379:methods*; D005006:Ethnicity / Q000706:statistics & numerical data*; D005163:Factor Analysis, Statistical; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D011788:Quality of Life; D044469:Racial Groups / Q000706:statistics & numerical data*