Quantile regression is one of the alternative regression techniques used when the assumptions of classical regression analysis are not met, and it estimates the values of the study variable in various quantiles of the distribution. This study proposes ratio-type estimators of a population mean using the information on quantile regression for stratified random sampling. The proposed ratio-type estimators are investigated with the help of the mean square error equations. Efficiency comparisons between the proposed estimators and classical estimators are presented in certain conditions. Under these obtained conditions, it is seen that the proposed estimators outperform the classical estimators. In addition, the theoretical results are supported by a real data application.

Poisson regression model is the most common method used to model count response in many studies. This paper proposes a new ratio-type estimators based on Poisson regression in simple random sampling. The mean square error (MSE) equation of these estimators is obtained in this study. Theoretically, the MSE of the proposed estimators and the MSE of the traditional ratio estimators are compared. As a result of these comparisons, it has shown that the suggested estimator is more efficient than the traditional estimators. In addition, the results of the application part supported the theoretical findings of the study.

Poisson regression is used to deal with count data. The Poisson regression ratio estimator of the population mean is extended from single to double sampling. This is made possible by the provision of the population mean of an auxiliary variable. The mean square errors of the proposed estimators are expressed up to the first order. Theoretical and numerical results demonstrate that the proposed double-sampling Poisson-regression ratio estimator has a lower mean square error than the double-ratio and the single-sampling estimator. For Covid-19, the minimum mean square errors yielded by the proposed estimator of the total number of cases are 0.095 cases per day and 67.8 cases, compared with 0.112 cases per day and 84.8 cases with the double-ratio estimator.

The negative binomial regression model is a widely adopted approach when dealing with dependent variables that consist of non-negative integers or counts. This model serves as an alternative regression technique for addressing issues related to overdispersion in count data. Typically, the maximum likelihood estimator is employed to estimate the parameters of the negative binomial regression model. However, the maximum likelihood estimator can be highly sensitive to multicollinearity, leading to unreliable results. To eliminate the adverse effects of multicollinearity in the negative binomial regression model, we propose the use of a jackknife version of the Kibria–Lukman estimator. In this study, we conducted a theoretical comparison between the proposed jackknife Kibria–Lukman negative binomial regression estimator and several existing estimators documented in the literature. To assess the performance of the proposed estimator, we conducted two simulation studies and performed a real data application. The results from both the simulation studies and the real data application consistently demonstrated that the proposed jackknife Kibria–Lukman negative binomial regression estimator outperforms other estimators.

Purpose: Sport is an important tool in improving the quality of life of individuals with disabilities. The study aim to examine the life quality of individuals with physical disabilities with different functionality levels in relation to sports. Methods: A total of 36 individuals with physical disabilities participated in the study. The participants included individuals without any regular exercise (non-sportive, NS), those who played Boccia (B), and persons who played Wheelchair basketball (WCB) who could not provide independent ambulation. The Rivermead Mobility Index (RMI), Functional Independency Measurement (FIM), Trunk Impairment Scale (TIS), and World Health Organization Quality of Life Instrument for People with Intellectual and Physical Disabilities (WHOQOL-DIS) were used for evaluating motor impairment of the trunk, functionality levels, mobility, and quality of life (QoL), respectively. Results: Group B had lower RMI scores compared to group NS (p0.05), but higher in the WCB group (p

Zeynep Yegin, Gokhan Sarisoy, Ahmet Uzun, Haydar Koc. Clin Psychopharmacol Neurosci 2024;22:655-61. https://doi.org/10.9758/cpn.24.1201