Socio-Economic Characteristics of Female Population in Usilampatti Taluk, Madurai District Using Multivariate Analysis and Structural Equation Model

Authors

  • S. Valarmathi  Research Scholar Department of Geography, Madurai Kamaraj University, Madurai, Tamil Nadu, India
  • Dr. I. K. Manonmani  Assistant Professor Department of Geography, Madurai Kamaraj University, Madurai, Tamil Nadu, India
  • Dr. S. Vadivel  Assistant Professor, Post Graduate and Research Department of Geography, Government Arts College (Autonomous), Kumbakonam, Tamil Nadu, India

Keywords:

Female Population Characteristic, Structural Eduation Modeling, Factor Analysis

Abstract

The female population characteristic of any area or region is a significant reflection of physical, economic, social justice conditions and availability of the resources. Women’s status is often described in terms of their level of education, employment, income, and health as well as their roles within the family and the society. In view of this chapter has been analyzed using systematic socio spatial analysis by means of a structural eduation modeling and factor analysis to extract various aspects of the female population characteristic in the Usilampatti Taluk.

References

  1. Anderson JC, and Gerbing DW (1988). Structural equation modelling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411–423.
  2. Bollen, KA. (1989b). Structural equations with latent variables. New York: John Wiley and Sons.
  3. Chauhan Poonam (2003), "Status of Women in India", Manan Publications Private limited, New Delhi, India, pp. 75-80
  4. Duncan TE, Duncan SC, Alpert A, Hops H, Stoolmiller M and Muthen B (1997). Latent variable modelling of longitudinal and multilevel substance use data. Multivariate Behavioural Research, 32(3), 275-318.
  5. Fan X, Thompson B, Wang L (1999). Effects of Sample Size, Estimation Methods, and Model Specification on Structural Equation Modelling Fit Indexes. Struct. Equ. Model. 6(1):56-83.
  6. Gerbing DW, Anderson JC (1992). Monte Carlo evaluations of goodness of fit indices for structural equation models. Social. Methods Res. 21(2):132–160.
  7. Hair JF, Anderson RE, Tatham RL, Black WC (1998). Multivariate Data Analysis, Prentice- Hall, Upper Saddle River, New Jersey. In: Marcin Pont and Lisa McQuilken (2002). Testing the Fit of the BANKSERV Model to BANKPERF Data. ANZMAG conference proceedings.865.
  8. Hooper D, Coughlan J, Mullen MR (2008). "Structural Equation Modelling: Guidelines for Determining Model Fit." The Electronic Journal of Business Research Methods. 6 (1): 53 – 60
  9. Hu LT, Bentler PM (1999). Cut off Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives, Struct. Equ. Model. 6(1):1-55.
  10. Peter T (2011). Adoption of Mobile money technology: Structural Equation Modelling Approach. Eur. J. Bus. Manage. 3(7):2011.
  11. Pillai Khothari Jaya (2003), "Women and Empowerment", Gyan Publication House, New Delhi, India, pp. 25-30. 
  12. Wegmann KM, Thompson AM and Bowen NK (2011). A Confirmatory factor analysis of home environment and home social behaviour data from the ESSP for Families. Social Work Research, 35, 117–127.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2018-04-30

Issue

Volume 4, Issue 4, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
S. Valarmathi, Dr. I. K. Manonmani, Dr. S. Vadivel, " Socio-Economic Characteristics of Female Population in Usilampatti Taluk, Madurai District Using Multivariate Analysis and Structural Equation Model , International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 4, pp.747-749, March-April-2018.