Item Response Theory (IRT) models have been
extensively used in the field of education to identify link between a response
to a test item and underlying latent capability of the test taker. We
demonstrate the benefit of using IRT model to analyze health data using data
from M.chat
program such that statisticians can use the method in lieu of traditional
methods including Cronbach’s alpha, discriminant analysis and factor analysis.
M.chat is
a technology based health coaching program and the baseline survey from the participants
in the program includes response in different but correlated domains of diet, social habits, leisure
practices, mental health, substance abuse, self-sufficiency and medication
adherence. We analyzed baseline data from 416 subjects using IRT models. Our
results indicated that responses pertaining to alcohol and substance abuse were
the most discriminating items with an average discrimination estimate of
approximately 4.99 whereas the least discriminating items were the diet habits,
with an average estimate of -0.476.
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