In social and health sciences, many statistical procedures and estimation techniques rely on the underlying distributional assumption of normality of the data. Non-normality may lead to incorrect statistical inferences. This study evaluates the performance of selected normality tests within the stringency framework for skewed alternative space. The stringency concept allows us to rank the tests uniquely. The Bonett and Seier test (Tw) turns out to represent the best statistics for slightly skewed alternatives and the Anderson–Darling (AD); Chen–Shapiro (CS); Shapiro–Wilk (W); and Bispo, Marques, and Pestana (BCMR) statistics are the best choices for moderately skewed alternative distributions. The maximum loss of Jarque–Bera (JB) and its robust form (RJB), in terms of deviations from the power envelope, is greater than 50%, even for large sample sizes, which makes them less attractive in testing the hypothesis of normality against the moderately skewed alternatives. On balance, all selected normality tests except Tw and Daniele Coin’s COIN-test performed exceptionally well against the highly skewed alternative space.
A topological index, also known as connectivity index, is a molecular structure descriptor calculated from a molecular graph of a chemical compound which characterizes its topology. Various topological indices are categorized based on their degree, distance, and spectrum. In this study, we calculated and analyzed the degree-based topological indices such as first general Zagreb index M r G , geometric arithmetic index GA G , harmonic index H G , general version of harmonic index H r G , sum connectivity index λ G , general sum connectivity index λ r G , forgotten topological index F G , and many more for the Robertson apex graph. Additionally, we calculated the newly developed topological indices such as the AG 2 G and Sanskruti index for the Robertson apex graph G.
Background: Workers in the textile industry risk developing various respiratory and pulmonary diseases due to exposure to cotton dust. The particles from the cotton lint are inhaled by the workers and results in the breathing problems including asthma, shortness of breath, cough and tightness in the chest. The poor health of labor contributes to the low productivity of the labor and in serious cases loss of jobs leading to the poverty. Objective: To assess the prevalence of respiratory symptoms among the textile workers and associated community. To contrast the health profiles of the textile workers, associated community and the control group to factor out any confounding factors. Methods: This study explores the health profiles of the textile workers and associated community and contrast them against the health profile of the control group to factor out any confounding factors. The study is conducted on cotton industry in Kasur, Pakistan. We interviewed 207 workers, 226 people from associated community (living in vicinities of weaving units) and 188 people for control group (from areas far away from weaving units and people are not associated with weaving industry) based on stratified random sampling technique. We employed descriptive methods and logistic regression to explore the association between respiratory diseases and weaving workers. Results: Overall, prevalence of postnasal drip, byssinosis, asthma, and chronic bronchitis were 47%, 35%, 20%, and 10%, respectively, among the workers. These percentages are significantly higher than the control group. An additional year of work increase the risk of postnasal drip, byssinosis, asthma, and chronic bronchitis by 5–6%. Among workers, 43% and 21% feel difficulty in hearing against noisy background and at low volume, respectively. Due to bad light arrangements at workstations, 21% and 31% workers are suffering from myopia and hyperopia, respectively. Proportions of the workers suffering from continuous headache, skin infection, depression, and low back pain are 28%, 29%, 27%, and 44%, respectively. Chi-square test results confirms that no confounding factor like air pollution is involved in this cause-and-effect study implying the association between the cotton dust and associated diseases is not spurious. Conclusion: Respiratory symptoms were statistically significantly more common in the weaving workers compared to control group. Better environment at workstations, use of protective gears and education are the factors which reduce the risk of associated diseases among workers.
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