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Updated: Aug 2, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Prediction of premorbid intellectual functioning of young children using demographic information
A H Sellers1, W J Burns, J S Guyrke
1Center for Psychological Studies, Nova Southeastern University, Ft. Lauderdale, Florida 33314, USA.
Abstract:
Regression equations were developed for the estimation of Wechsler Preschool and Primary Scale of Intelligence - Revised (WPPSI-R) Verbal, Performance and Full Scale IQs from the demographic characteristics of the WPPSI-R standardization sample (N=1700) Parent's education level, child's ethnicity, parent's occupation, and geographic region were found to be most predictive of the IQs The three resultant models produced statistically significant Rs of 0 54, 0 52, and 0 44 for Full, Verbal and Performance scales, respectively All three models showed minimal shrinkage upon crossvalidation, but results of tests for similarity of magnitude, variation, and classification were considerably poorer Guidelines and cautions for the clinical use of these models are discussed Also, the results are discussed in the context of similar studies.
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