Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey

Hande Ünlü; Serpil Aktaş

doi:10.30931/jetas.321165

Research Article

Year 2017, Volume: 2 Issue: 2, 101 - 111, 09.10.2017

Hande Ünlü Serpil Aktaş

https://doi.org/10.30931/jetas.321165

Cited By: 11

Abstract

References

[1] Ferrari S. , Cribari-Neto, F. Beta Regression for Modelling Rates and Proportions, Journal of Applied Statistics, 31(7) (2004): 799-815.
[2] Swearingen, C.J., Castro, M.S.M. & Bursac, Z. Modeling percentage outcomes: the %Beta Regression macro. SAS Global Forum 2011, (2011) Paper 335-2011. Available at http://support.sas.com/resources/papers/proceedings11/335-2011.pdf.
[3] Smithson M, Verkuilen J. A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables. Psychol Methods, 11(1) (2006):54–71.
[4] Ospina, R., Cribari-Neto, F., and Vasconcellos, K.LP. Improved point and interval estimation for a beta regression model. Computational Statistics & Data Analysis, 51(2) (2006):960–981.
[5] Paolino P. Maximum likelihood estimation of models with beta-distributed dependent variables. Political Analysis, 9(2011):325-346.
[6] Kieschnick R, McCullough BD. Regression analysis of variates observed on (0,1): percentages, proportions and fractions. Statistical Modelling, 3(2003):193-213.
[7] Rocha AV, Simas AB.. Influence diagnostics in a general class of beta regression models. Test, epub 23.Swearingen CJ, Melguizo castro MS, and Bursac Z. Modeling percentage outcomes: The %Beta_Regression macro. SAS® Global Forum Proceedings (2011); Paper 335:1–12.
[8] Cribari-Neto F, Zeileis A. Beta Regression in R.” Journal of Statistical Software, 34(2) (2010) 1–24.
[9] IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.
[10] McCullagh, P. and Nelder, J. A. Generalized Linear Models. Chapman & Hall, London, 2nd edition (1989).

Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey

Year 2017, Volume: 2 Issue: 2, 101 - 111, 09.10.2017

Hande Ünlü Serpil Aktaş

https://doi.org/10.30931/jetas.321165

Cited By: 11

Abstract

Beta regression assumes that the dependent variable follows a beta distribution and that its mean is related to a set of exploratory variables through a linear predictor with unknown coefficients and a link function. The model also includes a dispersion parameter. This paper describes the beta regression model along with its properties. The application of the model is made on well-being index data of Turkey 2015, which comprise the dimensions of housing, work, income and wealth, health, education, environment, safety, civic participation and access to infrastructure services and social life. As the life satisfaction index lies between 0 and 1 and the values close to 1 refers to a better level of life. Beta regression fits the data well and the regression parameters are well interpreted in terms of the mean of the response variable.

Keywords

beta distribution, beta regression, dispersion parameter

References

[1] Ferrari S. , Cribari-Neto, F. Beta Regression for Modelling Rates and Proportions, Journal of Applied Statistics, 31(7) (2004): 799-815.
[2] Swearingen, C.J., Castro, M.S.M. & Bursac, Z. Modeling percentage outcomes: the %Beta Regression macro. SAS Global Forum 2011, (2011) Paper 335-2011. Available at http://support.sas.com/resources/papers/proceedings11/335-2011.pdf.
[3] Smithson M, Verkuilen J. A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables. Psychol Methods, 11(1) (2006):54–71.
[4] Ospina, R., Cribari-Neto, F., and Vasconcellos, K.LP. Improved point and interval estimation for a beta regression model. Computational Statistics & Data Analysis, 51(2) (2006):960–981.
[5] Paolino P. Maximum likelihood estimation of models with beta-distributed dependent variables. Political Analysis, 9(2011):325-346.
[6] Kieschnick R, McCullough BD. Regression analysis of variates observed on (0,1): percentages, proportions and fractions. Statistical Modelling, 3(2003):193-213.
[7] Rocha AV, Simas AB.. Influence diagnostics in a general class of beta regression models. Test, epub 23.Swearingen CJ, Melguizo castro MS, and Bursac Z. Modeling percentage outcomes: The %Beta_Regression macro. SAS® Global Forum Proceedings (2011); Paper 335:1–12.
[8] Cribari-Neto F, Zeileis A. Beta Regression in R.” Journal of Statistical Software, 34(2) (2010) 1–24.
[9] IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.
[10] McCullagh, P. and Nelder, J. A. Generalized Linear Models. Chapman & Hall, London, 2nd edition (1989).

There are 10 citations in total.

Details

Primary Language	English
Subjects	Mathematical Sciences
Journal Section	Research Article
Authors	Hande Ünlü Serpil Aktaş
Publication Date	October 9, 2017
Published in Issue	Year 2017 Volume: 2 Issue: 2

Cite

APA	Ünlü, H., & Aktaş, S. (2017). Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey. Journal of Engineering Technology and Applied Sciences, 2(2), 101-111. https://doi.org/10.30931/jetas.321165
AMA	Ünlü H, Aktaş S. Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey. JETAS. October 2017;2(2):101-111. doi:10.30931/jetas.321165
Chicago	Ünlü, Hande, and Serpil Aktaş. “Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey”. Journal of Engineering Technology and Applied Sciences 2, no. 2 (October 2017): 101-11. https://doi.org/10.30931/jetas.321165.
EndNote	Ünlü H, Aktaş S (October 1, 2017) Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey. Journal of Engineering Technology and Applied Sciences 2 2 101–111.
IEEE	H. Ünlü and S. Aktaş, “Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey”, JETAS, vol. 2, no. 2, pp. 101–111, 2017, doi: 10.30931/jetas.321165.
ISNAD	Ünlü, Hande - Aktaş, Serpil. “Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey”. Journal of Engineering Technology and Applied Sciences 2/2 (October 2017), 101-111. https://doi.org/10.30931/jetas.321165.
JAMA	Ünlü H, Aktaş S. Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey. JETAS. 2017;2:101–111.
MLA	Ünlü, Hande and Serpil Aktaş. “Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey”. Journal of Engineering Technology and Applied Sciences, vol. 2, no. 2, 2017, pp. 101-1, doi:10.30931/jetas.321165.
Vancouver	Ünlü H, Aktaş S. Beta Regression for the Indicator Values of Well-Being Index For Provinces in Turkey. JETAS. 2017;2(2):101-1.