On Improving Ratio/Product Estimator by Ratio/Product-cum-Mean-per-Unit Estimator Targeting More Efficient Use of Auxiliary Information

To achieve a more efficient use of auxiliary information we propose single-parameter ratio/product-cum-mean-per-unit estimators for a finite population mean in a simple random sample without replacement when the magnitude of the correlation coefficient is not very high (less than or equal to 0.7). The first order large sample approximation to the bias and the mean square error of our proposed estimators are obtained. We use simulation to compare our estimators with the well-known sample mean, ratio, and product estimators, as well as the classical linear regression estimator for efficient use of auxiliary information. The results are conforming to our motivating aim behind our proposition

Electronic Cigarette Use Among Emerging and Young West Indian Adults

Currently, evidence concerning electronic cigarette (e-cigarette) use in the West Indies is unavailable. This study examines the prevalence and associated factors of e-cigarette use in young Trinidadian adults, 6 years after e-cigarettes were introduced in Trinidad. Young adults between the ages of 18 and 40 years were surveyed from May–June 2016. Based on the survey results, descriptive statistics and logistic regression models were used to identify correlations in e-cigarette use. The prevalence of those who had used e-cigarettes was 24.6%, and 41.9% of these people had used both e-cigarettes and tobacco cigarettes. A high proportion (16.95%) of those who had never used tobacco cigarettes had used e-cigarettes. Males were twice as likely as females to have used e-cigarettes (odds ratio [OR]: 2.60; 95% confidence interval [CI]: 1.85–3.68), and participants aged 18–25 years were more likely than those aged 36–40 years to use e-cigarettes (OR: 0.37; 95% CI: 0.14–0.81). The predictors of e-cigarette use as assessed by univariate analysis were current tobacco cigarette smoking (OR: 9.34; 95% CI: 6.14–14.39; p<0.001) and the belief that e-cigarettes are dangerous to health (OR: 0.61; 95% CI: 0.44–0.85; p=0.004). The predictors as assessed by multivariate logistic regression (adjusted OR) were ethnicity (p=0.043), education (p=0.012), and age group (p=0.007). Those who quit using tobacco cigarettes were 7.98 times more likely to use e-cigarettes (95% CI: 4.21–15.45), and those who knew that e-cigarettes contain nicotine were 2.70 times more likely to use them (95% CI: 1.53–4.86; p<0.001). Two summative scales were constructed that measured knowledge and perception. The perception scale, but not the knowledge scale (Cronbach’s alpha=0.736), was a significant predictor of e-cigarette use. The number of e-cigarette users is high (24.6%) in young adults in Trinidad and in those who have never smoked tobacco (16.95%). Current smokers, as well as those who have quit smoking, are at an increased risk of e-cigarette use. This study established that young adults have a low level of knowledge regarding e-cigarettes and shows that they should be educated on e-cigarette use. Further research to examine the reasons for, and susceptibility to, e-cigarette use is necessary

Investigating the influence of fans on home advantage outcomes in association football across Europe

Fan support has long been stated as one of the major contributors to the home advantage which football teams enjoy across Europe; whereby fans motivate the home team to increase performance levels, and in some cases, inadvertently cause referees to subconsciously make decisions in favour of the home team. With the naturally created experimental design by the COVID-19 pandemic, the unique opportunity arose to analyse the influence of fans on these home advantage outcomes. Mixed-effects models were used while controlling for available confounds. It was observed that home teams won fewer points and were less dominant without the support of their fans; while referees called more fouls against, and produced more yellow cards for home teams without fans present. However, these decisions were dependent on team dominance in a match. The findings reinforced social theories and also provided greater insights into the home advantage phenomenon

Improving the efficiency of the ratio/product estimators of the population mean in stratified random samples

The efficiency of a statistic determines its efficacy. In stratified random sampling, many estimators for the population mean has been proposed. In this paper, we propose two new estimators both of which are combined ratio/product estimators. We refer to our estimators as mixture estimators. We derive the mean square errors (MSEs) up to the first order. A comprehensive simulation study was carried out to show the effectiveness of our estimators as compared to the conventional estimators that utilize auxiliary information. We also compared the performance of our estimators and some of the more popular competing estimators using real data. Both the simulations and real data analysis showed our estimators were more efficient than almost all existing estimators considered