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Kumaraswamy Regression Modeling for Bounded Outcome Scores Publisher



Hamedishahraki S1 ; Rasekhi A2 ; Eshraghian MR3 ; Yekaninejad MS3 ; Pakpour AH4
Authors
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Authors Affiliations
  1. 1. Department of Epidemiology and Biostatistics, School of Public Health, Zabol University of Medical Sciences, Zabol, Iran
  2. 2. Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
  3. 3. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Social Determinants of Health Research Center, Qazvin University of Medical Sciences, Shahid Bahounar, Qazvin, Iran

Source: Pakistan Journal of Statistics and Operation Research Published:2021


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. © 2021. All Rights Reserved.