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Abstract: In clinical trials, sample size is usually lesser as compared to other epidemiological studies to make it more feasible and cost effective. Small sizes of such trials discourage the use of parametric test due to violation of the assumption under which they are applicable. Therefore, the use of nonparametric test is substantial in clinical trials to test two or more independent samples. The Kruskal-Wallis h test is an alternative to one-way ANOVA and can be used to identify significant differences among different populations. When we have several independent samples and assumed to be arranged orderly, Jonckheere Terpstra test is a best choice to compare population medians instead of means. For the application of Jonckheere Terpstra test the data from the study of cleaning methods for ultrasound probes are used. The Jonckheere Terpstra test is recommended over Kruskal-Wallis h test as it compares and provides significant difference between more than two population medians when they arranged in order. Therefore, the aim of this research paper was to explore the use and significance of Jonckheere-Terpstra test with the use of practical example. Keywords: Jonckheere Terpstra test, non parametric test, comparison of medians. Download Full Article |
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Abstract: Propensity score matching is a useful tool to analyze observational data in clinical investigations, but it is often executed in an overly simplistic manner, failing to use the data in the best possible way. This review discusses current best practices in propensity score matching, outlining the method’s essential steps, including appropriate post-matching balance assessments and sensitivity analyses. These steps are summarized as eight key traits of a propensity matched study. Further, this review illustrates these traits through a case study examining the impact of access site in percutaneous coronary intervention (PCI) procedures on bleeding complications. Through propensity score matching, we find that bleeding occurs significantly less often with radial access procedures, though many other outcomes show no significant difference by access site, a finding that mirrors the results of randomized controlled trials. Lack of attention to methodological principles can result in results that are not biologically plausible. Keywords: Propensity Score Matching, Observational Data, Clinical Investigations. Download Full Article |
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Abstract: Editorial Download Full Article |
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Abstract: In this study, some important issues regarding process capability and performance have been highlighted, particularly in case when the distribution of a process characteristic is non-normal. The process capability and performance analysis has become an inevitable step in quality management of modern industrial processes. Determination of the performance capability of a stable process using the standard process capability indices (Cp, Cpk) requires that the quality characteristics of the underlying process data should follow a normal distribution. Statistical Process Control charts widely used in industry and services by quality professionals require that the quality characteristic being monitored is normally distributed. If, in contrast, the distribution of this characteristic is not normal, any conclusion drawn from control charts on the stability of the process may be misleading and erroneous. In this paper, an alternative approach has been suggested that is based on the identification of the best distribution that would fit the data. Specifically, the Johnson distribution was used as a model to normalize real field data that showed departure from normality. Real field data from the construction industry was used as a case study to illustrate the proposed analysis. Keywords: Statistical Process Control, Shewhart control charts, non-normal data, Johnson System of distributions. Download Full Article |
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Abstract: The generalized linear model is an important class of models that has wide variety of applications mainly because of its inherent flexibility and generality. The present paper provides an important application of GLM in order to examine different constituents of bile acid in the development of gallstones as well as carcinoma among the gallbladder patients. These constituents may be broadly categorized as primary and secondary bile acids. The paper, in fact, considers two particular cases of GLM based on normal and gamma modelling assumptions and provides the complete Bayes analysis using independent but vague priors for the concerned model parameters. It then analyzes a real data set taken from SS Hospital, Banaras Hindu University, with primary (secondary) bile acids as response variables and secondary (primary) bile acids as the predictors. The authenticity of the assumed models for the given data set is also examined based on predictive simulation ideas. Keywords: Generalized linear model, vague priors, posterior distribution, biliary acids, gallbladder diseases, predictive simulation, Bayes information criterion. Download Full Article |