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Age-stratified norms for Raven’s standard progressive matrices for Sri Lankan adults.
- Source :
-
Clinical Neuropsychologist . Jun2024, p1-15. 15p. 2 Illustrations. - Publication Year :
- 2024
-
Abstract
- AbstractObjectiveMethodsResultsConclusionsThe aim of this study was to create age-stratified norms for the Raven’s Standard Progressive Matrices (SPM) for Sri Lankan adults.A sample of 610 adults (age: 18–72 years; education: 1–19 years), underwent the 60-item version of the SPM under individual supervision of a test administrator. The sample was stratified into 5-year age bands, and the norms are presented as percentile tables and percentile curves.The age-related changes were more accurately predicted by a curvilinear model (overall <italic>R</italic>2 = 0.961) than a linear regression model (<italic>R</italic>2 = 0.639). The SPM norms are presented as age-stratified percentile tables, as well as sex-, age- and education-adjusted multiple regression equations. The highest percentiles in the younger end of the age spectrum showed a ceiling effect. In the context of age-stratified US (1993) and British (1992) norms, older individuals in the Sri Lankan sample scored much lower than their Western counterparts. However, the difference narrowed in the younger age bands, showing no difference among the 18-to-22-year age bands in the three countries.This age-by-country interaction can be partly explained by poorer education in the older individuals in the present sample compared to those in the US and UK standardization samples. SPM norms presented in this paper fill a hiatus in assessment of general intellectual ability in Sri Lankan adults. Given that Sri Lanka improves its educational, socioeconomic and health standards faster than the nations who have already reached higher standards, these norms would require re-standardization in the coming decades. [ABSTRACT FROM AUTHOR]
- Subjects :
- *OLDER people
*ADULTS
*REGRESSION analysis
*PERCENTILES
Subjects
Details
- Language :
- English
- ISSN :
- 13854046
- Database :
- Academic Search Index
- Journal :
- Clinical Neuropsychologist
- Publication Type :
- Academic Journal
- Accession number :
- 178113203
- Full Text :
- https://doi.org/10.1080/13854046.2024.2370908