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Direct linkBroda, Michael D.; Bogenschutz, Matthew; Dinora, Parthenia; Prohn, Seb M.; Lineberry, Sarah; Ross, Erica – American Journal on Intellectual and Developmental Disabilities, 2021
In this article, we demonstrate the potential of machine learning approaches as inductive analytic tools for expanding our current evidence base for policy making and practice that affects people with intellectual and developmental disabilities (IDD). Using data from the National Core Indicators In-Person Survey (NCI-IPS), a nationally validated…
Descriptors: Artificial Intelligence, Prediction, Employment Patterns, Day Programs
Stancliffe, Roger J.; Kramme, Julie E. D.; Nye-Lengerman, Kelly – Intellectual and Developmental Disabilities, 2018
To begin to understand retirement, we examined age-related differences in (a) employment rates, employment hours, and rates of individual-plan employment goals; and (b) participation rates in unpaid formal day programs. We report weighted analyses of 2014-15 National Core Indicators data from 32 states. Unlike younger age groups, a similar…
Descriptors: Retirement, Intellectual Disability, Developmental Disabilities, Older Workers
