Predicting employment outcomes of rehabilitation clients with orthopedic disabilities: A CHAID analysis

Abstract

The data mining approach (i.e., CHAID analysis) provided detailed information and insight about interactions among demographic variables, service patterns, and competitive employment rates through the segmentation of the sample into mutually exclusive homogeneous subgroups.

CHAID Analysis to Determine Socioeconomic Variables that Explain Students' Academic Success

“…A decision-tree method offers a number of advantages over more commonly used statistical techniques [38]. For instance, it is nonparametric and nonlinear.…”

“…Three algorithms can be used: CHAID, C&RT (Classification and Regression Trees) and QUEST (Quick, Unbiased, Efficient Statistical Tree). All of these algorithms are mainly used to outline the relationships between variables and statistically significant structures and divide the data sets into subgroups using decision rules [38,41]. The CHAID's advantages are that its output is highly visual and easy to interpret with multiple trees [42].…”

Genel Sağlik Durumunu Etki̇leyen Faktörleri̇n Chaid Anali̇zi̇ Yöntemi̇ İle İncelenmesi̇, Odtü Örneği̇

“…(2006), ortopedik engellilerin istihdam sonucunu etkileyen faktörleri Chaid algoritması yardımıyla incelemişlerdir [5]. Kayri Çözüm sonuçlarına bakıldığında ilk düğümde çalışmanın bağımlı değişkeni olan "genel sağlık durumu" değişkeni yer almaktadır.…”

Characteristics of family caregivers with sleep dissatisfaction in Japan: Identification using CHAID dendrograms

“…The variable at the highest level of the tree is considered to have the closest statistical association with the dependent variable. The CHAID technique has traditionally been used in business and marketing research (20), and its use is increasing in rehabilitation and mental health studies (21,22).…”