Journal of Data Science

Although the two-parameter Beta distribution is the standard distribution for

Abstract: A family of distribution is proposed by using Kumaraswamy-G ( Kw − G ) distribution as the base line distribution in the generalized Marshall-Olkin (GMO) construction. By expanding the probability density function and the survival function as infinite series the proposed family is seen as infinite mixtures of the Kw − G distribution. Series expansions of the density function for order statistics are also obtained. Moments, moment generating function, Rényi entropy, quantile function, random sample generation, asymptotes, shapes and stochastic orderings are also investigated. Maximum likelihood estimation, their large sample standard error, confidence intervals and method of moment are presented. Three real life illustrations of comparative data modeling applications with some of the important sub mode

Factor analysis (FA) is the most commonly used pattern recognition methodology in social and health research. A technique that may help to better retrieve true information from FA is the rotation of the information axes. The purpose of this study was to evaluate whether the selection of rotation type affects the repeatability of the patterns derived from FA, under various scenarios of random error introduced, based on simulated data from the Standard Normal distribution. It was observed that when applying promax non - orthogonal rotation, the results were more repeatable as compared to the orthogonal rotation, irrespective of the level of random error introduced in the model.

Abstract: In the absence of definitive trials on the safety and efficacy of drugs, a systematic and careful synthesis of available data may provide critical information to help decision making by policy makers, medical professionals, patients and other stakeholders. However, uncritical and unbalanced use of pooled data to inform decision about important healthcare issues may have consequences that adversely impact public health, stifle innovation, and con found medical science. In this paper, we highlight current methodological issues and discuss advantages and disadvantages of alternative meta-analytic techniques. It is argued that results from pooled data analysis would have maximal reliability and usefulness in decision making if used in a holistic framework that includes presentation of data in light of all available knowledge and effective collaboration among academia, industry, regulatory bodies and other stakeholders.

Abstract: Childhood obesity is a major health concern. The associated health risks dramatically reduce lifespan and increase healthcare costs. The goal was to develop methodology to identify as early in life as possible whether or not a child would become obese at age five. This diagnostic tool would facilitate clinical monitoring to prevent and or minimize obesity. Obesity is measured by Body Mass Index (BMI), but an improved metric, the ratio of weight to height (or length) (WOH), is proposed from this re search for detecting early obesity. Results of this research demonstrate that WOH performs better than BMI for early detection of obesity in individuals using a longitudinal decision analysis (LDA), which is essentially an indi viduals type control chart analysis about a trend line. Utilizing LDA, the odds of obesity of a child at age five is indicated before the second birth day with 95% sensitivity and 97% specificity. Further, obesity at age five is indicated with 75% specificity before two months and with 84% specificity before three months of age. These results warrant expanding this study to larger cohorts of normal, overweight, and obese children at age five from different healthcare facilities to test the applicability of this novel diagnostic tool.

Abstract: Information identities derived from entropy and relative entropy can be useful in statistical inference. For discrete data analyses, a recent study by the authors showed that the fundamental likelihood structure with categorical variables can be expressed in different yet equivalent information decompositions in terms of relative entropy. This clarifies an essential difference between the classical analysis of variance and the analysis of discrete data, revealing a fallacy in the analysis of hierarchical loglinear models. The discussion here is focused on the likelihood information of a three-way contingency table, without loss of generality. A classical three-way categorical data example is examined to illustrate the findings.

Abstract: In this paper we endeavour to provide a largely non-technical description of the issues surrounding unbalanced factorial ANOVA and review the arguments made for and against the use of Type I, Type II and Type III sums of squares. Though the issue of which is the `best' approach has been debated in the literature for decades, to date confusion remains around how the procedures differ and which is most appropriate. We ultimately recommend use of the Type II sums of squares for analysis of main effects because when no interaction is present it tests meaningful hypotheses and is the most statistically powerful alternative.

Abstract: Despite the availability of software for interactive graphics, current survey processing systems make limited use of this modern tool. Interactive graphics offer insights, which are difficult to obtain with traditional statis tical tools. This paper shows the use of interactive graphics for analysing survey data. Using Labour Force Survey data from Pakistan, we describe how plotting data in different ways and using interactive tools enables analysts to obtain information from the dataset that would normally not be possible using standard statistical methods. It is also shown that interacative graphics can help the analyst to improve data quality by identifying erroneous cases.

Providing a new distribution is always precious for statisticians. A new three parameter distribution called the gamma normal distribution is defined and studied. Various structural properties of the new distribution are derived, including some explicit expressions for the moments, quantile and generating functions, mean deviations, probability weighted moments and two types of entropy. We also investigate the order statistics and their moments. Maximum likelihood techniques are used to fit the new model and to show its potentiality by means of two examples of real data. Based on three criteria, the proposed distribution provides a better fit then the skew-normal distribution.