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Extensive research work has been done for the estimation of population mean using bivariate auxiliary information based on conventional measures. Conventional measures of the auxiliary variables provide suspicious results in the presence of outliers/extreme values. However, non-conventional measures of the auxiliary variables include quartile deviation, mid-range, inter-quartile range, quartile average, tri-mean, Hodge-Lehmann estimator etc. give efficient results in case of extreme values. Unfortunately, non-conventional measures are not used by survey practitioners to enhance the estimation of unknown population parameters using bivariate auxiliary information. In this article, difference-cum-exponential-type estimators for population mean utilizing bivariate auxiliary information based on non-conventional measures under simple and stratified random sampling schemes have been suggested. Mathematical properties such as bias and mean squared error are derived. To support theoretical findings, various real-life applications are used to confirm the superiority of the suggested estimators as compared to the competing estimators under study. [ABSTRACT FROM AUTHOR]

The Power Function distribution is one of the most suitable distributions for failure times modeling, especially of electric components and devices. The article proposes some new modified estimators for parameter estimation of the Power Function distribution. The proposed modified estimators are based on the mean and geometric mean of the distribution. The performance of these estimators is compared with existing traditional and modified estimators by means of Monte Carlo simulation and two real‐life examples. Total mean square error, total relative deviation, root mean square error and mean absolute error are used as performance criteria. The performance of the estimators is also compared on two real‐life data sets repressing the device failures times. From both, Monte Carlo simulation and real‐life applications, the results indicated that the proposed modified estimators perform better than the competing estimators and hence their use is recommended for parameter estimation of the Power Function probability model. The findings will help to get more precise parameter estimates for the distribution which is very much applied in different fields particularly in modelling failure times of electronic devices and components. [ABSTRACT FROM AUTHOR]

Objective: To determine the frequency of sodium and potassium abnormalities associated with acute gastroenteritis in children and its complications. Study Design: Cross sectional study. Place and Duration of Study: Pediatric Medicine Department of Shaikh Zayed Hospital, Lahore, from Jan to Dec 2019. Methodology: Two hundred and eighteen children were recruited in the study according to inclusion and exclusion criteria. After taking informed consent, their demographic data recorded, blood samples were taken and examined for serum sodium and potassium levels. The complications arising from sodium and potassium abnormalities were also noted. Results: There were 101 (46.3%) males while 117 (53.7%) females with male to female ratio of 1:1.2. Mean age was 1.87 ± 1.30 years. 42 (19.2%) children had sodium abnormality, 93 (42.7%) children had potassium abnormalities and 83 (38.1%) children had no abnormality. Out of 29 (13.3%) children had complications while 189 (86.7%) children were without complications. Conclusion: We concluded that 42 (19.2%) children had sodium abnormality, 93 (42.7%) children had potassium abnormalities and 13.3% patients developed complication. This can be prevented by implementing hygienic practices, routine vaccinations and prompt rehydration. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to identify the accelerators of sharing economy that lead to sustainability by adopting green consumption. Nostalgia is studied as a mediator along with social connectedness and past orientation. Specifically, the study is based upon a framework to explore the outcomes of sharing economy through an individual's green consumption behavior from the perspective of mortality anxiety. Design/methodology/approach: Quantitative research technique was employed by collecting data from 537 households through snowball sampling. The model was tested using partial least squares (SEM-VB). The validity of the theoretical and measurement model was assessed. Findings: The results revealed that nostalgia positively influences social connectedness and past orientation, whereas social connectedness and past orientation accelerate green consumption. However, it was confirmed that nostalgia decreases green consumption. Research limitations/implications: The drivers of sharing economy lead toward environmentally friendly consumer behavior by providing opportunities for different agents to increase the usage of shared consumption. The model can be improved by introducing other mediating variables to enrich understanding. Practical implications: The study may provide opportunities for practitioners and the government to identify the key factors in a sharing economy, specifically with reference to green consumption and social connectedness. It is predicted that it will help reduce environmental deterioration. Originality/value: This study identifies the role of mortality anxiety and nostalgia toward green consumption, predominantly in the context of a sharing economy. It is a forward to collaborative consumption. [ABSTRACT FROM AUTHOR]