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Kumaraswamy regression modeling for Bounded Outcome Scores
Author(s):
1. Soudabeh Hamedi-Shahraki: . Department of Epidemiology and Biostatistics, School of Public Health, Zabol University of Medical Sciences,Zabol,Iran
2. Aliakbar Rasekhi: . Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University,Tehran,Iran
3. Mohammad Reza Eshraghian: . Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences,Tehran,Iran
4. Mir Saeed Yekaninejad: . Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences,Tehran,Iran
5. Amir H Pakpour: . Social Determinants of Health Research Center, Qazvin University of Medical Sciences,Shahid Bahounar, Qazvin,Iran
Abstract:
In this paper, we use a regression model for modeling bounded outcome scores (BOS), where the outcome is Kumaraswamy distributed. Similar to the Beta distribution, this distribution can take a variety of shapes while being computationally easier to use. Thus, it is deemed as a suitable alternative distribution to the Beta in modeling bounded random processes. In the proposed model, the median of a bounded response is modeled by the linear predictors which are defined through regression parameters and explanatory variables. We obtained the maximum likelihood estimates (MLEs) of the parameters, provided closed-form expressions for the score functions and Fisher information matrix, and presented some diagnostic measures. We conducted Monte Carlo simulations to investigate the finite-sample performance of the MLEs of the parameters. Finally, two practical applications of this model to the real data sets are presented and discussed.
Page(s): 79-88
DOI: 10.18187/pjsor.v17i1.3411
Published: Journal: Pakistan Journal of Statistics and Operation Research, Volume: 17, Issue: 1, Year: 2021
Keywords:
Kumaraswamy distribution , Maximum Likelihood Estimation , diagnostic analysis , Beta regression , Bounded outcome score
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