CHAID Decision Tree: Methodological Frame and Application

Abstract

Technological advancement across human activities has brought about accelerated generation of huge amounts of data. Consequently, researchers are faced with the problem how to determine adequate ways of turning the available data mass into useful knowledge. Data analysis adapted to these changes when data mining was developed as an approach to data analysis from different perspectives which reveals significant hidden regularities. This paper presents conceptual characteristics of decision tree, an important data mining method which is, due to its explorative nature, exceptionally suitable for detection of data structure when analysing various problem situations. The empirical section of the paper demonstrates applicative characteristics of this method using CHAID algorithm in leadership studies: an interdependence of selected personal characteristics and the manager’s leadership style has been investigated. The aim of the paper is to develop a classification model for identification of the dominant leadership style. The study was conducted on the sample of 417 managers of privately owned small-sized enterprises in Serbia, using a specially designed questionnaire. The classification model identified the set of six statistically significant personal characteristics as predictors of dominant leadership style.

Socio-Economic Determinants of Land Use/Cover Change in Wetlands in East Africa: A Case Study Analysis of the Anyiko Wetland, Kenya

“…Unlike logistic regression, the CHAID algorithm explicitly express patterns among variables in a graphical and easily understandable form using the "if-then" logic (Au et al, 2003). The method can also identify the most important predictor of the dependent variable (Milanović and Stamenković, 2016). Therefore, the CHAID decision tree model is suitable for identifying stepwise pathways to wetland conversion to agriculture that would otherwise go unnoticed when logistic regression is employed.…”

Different Forms of Accommodation in Agritourism: The Role of Decoupled Farmer-Based Accommodation in the Ötztal Valley (Austria)

“…We used a CHAID decision tree on the basis of categorical data gathered through a cross-sectional survey [56] to apply our heuristic concept. CHAID is a form of multivariate analysis and consists of sequences of segmentation and summaries through cross-table analysis, where the interdependence between the input variables and output variable is evaluated through a predictor variable presented in the form of a tree [56,57]. The aim was to apply our heuristic concept to the identification of the types of farmer-based accommodation holdings through this data mining method [57].…”

“…The bivariate analysis was run through the Spearman correlation to test the interdependence of interval-scaled variables and Chi-Square tests to evaluate if there are statistically significant differences between the nominal scaled variables. A multivariate analysis was conducted through CHAID decision tree, which generates cross-table analysis sequences of segmentation and summaries and is presented in the form of a tree [56,57].…”

A Study on Governance and Development in Bodoland Territorial Area Districts of Assam in India

“…CHAID is a form of analysis that determines how continuous variables best combine to explain the outcome in a given dependent binary response variable. Hence, CHAID detects the association between the categorical dependent variable and multiple independent variables (Milanović et al 2016). In the present study, the response variable is the status of development i.e.…”