Usage as Complementary Correspondence Analysis and Logistic Regression in a  Scientific Survey on Self Healing Methods

Zerrin Asan Greenacre; Levent Terlemez; Sevil Sentürk

doi:10.4236/ojs.2014.411086

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Open Journal of Statistics > Vol.4 No.11, December 2014

Usage as Complementary Correspondence Analysis and Logistic Regression in a Scientific Survey on Self Healing Methods ()

Zerrin Asan Greenacre, Levent Terlemez, Sevil Sentürk

Statistic Department, Science Faculty, Anadolu Univesity, Eskisehir, Turkey.

DOI: 10.4236/ojs.2014.411086 PDF HTML XML 2,950 Downloads 3,560 Views Citations

Abstract

The aim of this study is to show complementary usage of logistic and correspondence analysis in a research subject to self-healing methodologies. Firstly, the number of the variables is reduced by logistic regression according to relationship between dependent and independent variables and then research carries on searching variables. The relationship among the behaviours of individuals and their demographic characteristics is modelled by logistic regression and shown graphically by correspondence analysis. In application, first of all, the effect of age, sex, marital status, education level, occupation and income level and present health condition, on appreciating self-health, is explained by a model. As a result of that model, it can be said that the effect of age, occupation and present health condition is reasonable. After analysing that model, the relationship between categorical variables (age, sex, occupation, preferred precautions, and worth of personal health) is shown graphically by multiple correspondence analysis.

Keywords

Logistic Regression, Correspondence Analysis, Self Healing

Share and Cite:

Greenacre, Z. , Terlemez, L. and Sentürk, S. (2014) Usage as Complementary Correspondence Analysis and Logistic Regression in a Scientific Survey on Self Healing Methods. Open Journal of Statistics, 4, 912-920. doi: 10.4236/ojs.2014.411086.

Conflicts of Interest

The authors declare no conflicts of interest.

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