Some statistical characteristics of special education for children with disabilities in North‐East India

Abstract

It is estimated that of approximately 150–250 million children with disabilities across the world, a large number have difficulties related to problems in the central nervous system (CNS). This paper considers school dropout rates of children with special educational needs associated with CNS problems from a study of educational institutions in North‐East India. Statistical methods, namely the Kaplan–Meier estimator (Product–Limit estimator) for survival probability and the Nelson–Aalen estimator for cumulative hazard rates, were used to identify potential school continuation or dropout probabilities (survival probabilities), along with cumulative hazard rates (dropout rates) for children with a range of disabilities from different training institutions within the sample area. The research found an increasing likelihood of increased dropout rates in relation to the age of the children within the study sample. This indicates that special education is yet to produce satisfactory results for these children.

Application of Epanechnikov kernel smoothing technique in disability data

“…In survival analysis, hazard rate plays an important role and is unique for all the distributions. These are used to understand the probabilistic pattern of an event (Kalita and Sarmah, 2012).…”