Modified maximum likelihood estimator under the Jones and Faddy's skew t-error distribution for censored regression model

It is well-known that classical Tobit estimator of the parameters of the censored regression (CR) model is inefficient in case of non-normal error terms. In this paper, we propose to use the modified maximum likelihood (MML) estimator under the Jones and Faddy''s skew t-error distribution, which covers a wide range of skew and symmetric distributions, for the CR model. The MML estimators, providing an alternative to the Tobit estimator, are explicitly expressed and they are asymptotically equivalent to the maximum likelihood estimator. A simulation study is conducted to compare the efficiencies of the MML estimators with the classical estimators such as the ordinary least squares, Tobit, censored least absolute deviations and symmetrically trimmed least squares estimators. The results of the simulation study show that the MML estimators work well among the others with respect to the root mean square error criterion for the CR model. A real life example is also provided to show the suitability of the MML methodology.     

Attitudes Toward Women in Health Care Organizations: A Turkish Case Study

Abstract

The aim of this article is to examine the health care employees’ attitudes toward women in health care organizations in Turkey. It was measured using a 25-item scale by Spence, Helmreich, and Stapp (1973 Spence, J. T., Helmreich, R., & Stapp, J. (1973). A short version of the Attitudes toward Women Scale (AWS). Bulletin of the Psychonomic Society, 2(4), 219–220. doi:10.3758/BF03329252[Crossref] , [Google Scholar]). The study was conducted on 541 employees: 279 males and 262 females. Structural equation model (SEM) was applied to analyze the relationship between gender, marital status, and income and attitudes toward woman. The result of this analysis showed that the relations between gender, marital status, and income and attitudes toward woman were statistically significant. All three hypotheses were statistically supported. This result indicated that employees’ marital status and (monthly) income significantly predicted their scores of attitudes toward woman in a positive direction. Besides, employees’ gender significantly predicted their scores of attitudes toward woman in an inverse direction. Future research can focus on investigating the effects of the attitudes toward women on other elements (e.g., performance, motivation, job satisfaction) or a wider sample to reach more generalized results.     

A new weighted distribution as an extension of the generalized half-normal distribution with applications

In this study, a new extension of generalized half-normal (GHN) distribution is introduced. Since this new distribution can be viewed as weighted version of GHN distribution, it is called as weighted generalized half-normal (WGHN) distribution. It is shown that WGHN distribution can be observed as a single constrained and hidden truncation model. Therefore, the new distribution is more flexible than the GHN distribution. Some statistical properties of the WGHN distribution are studied, i.e. moments, cumulative distribution function, hazard rate function are derived. Furthermore, maximum likelihood estimation of the parameters is considered. Some real-life data sets taken from the literature are modelled using the WGHN distribution. It is seen that for these data sets the WGHN distribution provides better fitting than the GHN and slashed generalized half-normal (SGHN) distributions.     

One-step M-estimators: Jones and Faddy's skewed t-distribution

One-step M (OSM)-estimator needs some initial/preliminary estimates at the beginning of the calculation process. In this study, we propose to use new initial estimates for the calculation of the OSM-estimator. We consider simple location and simple linear regression models when the distribution of the error terms is Jones and Faddy's skewed t. Monte-Carlo simulation study shows that the OSM estimator(s) based on the proposed initial estimates is/are more efficient than the OSM estimator(s) based on the traditional initial estimates especially for the skewed cases. We also analyze some real data sets taken from the literature at the end of the paper.