An evaluation of common methods for dichotomization of continuous variables to discriminate disease status

Dichotomization of continuous variables to discriminate a dichotomous outcome is often useful in statistical applications. If a true threshold for a continuous variable exists, the challenge is identifying it. This paper examines common methods for dichotomization to identify which ones recover a true threshold. We provide mathematical and numeric proofs demonstrating that maximizing the odds ratio, Youden’s statistic, Gini Index, chi-square statistic, relative risk and kappa statistic all theoretically recover a true threshold. A simulation study evaluating the ability of these statistics to recover a threshold when sampling from a population indicates that maximizing the chi-square statistic and Gini Index have the smallest bias and variability when the probability of being larger than the threshold is small while maximizing Kappa or Youden’s statistics is best when this probability is larger. Maximizing odds ratio is the most variable and biased of the methods.     

Acceptance sampling plans by variables for a class of symmetric distributions

The estimation of percentage defectives using a normal sampling plan will not be appropriate when the assumption of normality is violated. In this paper, we propose a sampling plan based on a more general symmetric family of distributions with the parameters estimated using the modified maximum likelihood (MML) procedures introduced by Tiku and Suresh . This sampling plan works well for most of the symmetric non-normal distributions. Some numerical study has also been carried out to show the superiority of the proposed plan.     

Bayesian analysis of prevalence from the results of small screening samples

Bayesian analysis is applied to the number of cases screened positive to estimate the disease prevalence and to predict the number of future cases with disease. The analysis makes use of additional experimental information about the test’s sensitivity and specificity and of prior information on the prevalence of disease. Prior and posterior probability distributions of disease prevalence are conjugate mixtures of Beta densities and can be expressed in exact algebraic form.     

Managing knowledge in supply chains: a catalyst to triple bottom line sustainability

Abstract

Sustainable supply chain management (SSCM) and knowledge management’s (KM) positive role in improving supply chain development and performance have both attracted attention in recent years, the former arguably stimulated by the triple bottom line (TBL). Despite the positive development, there is a paucity of theoretical and empirical studies identifying the broad capabilities that affect a firm’s ability to simultaneously pursue economic, environmental and social success. We use the natural-resource-based (NRBV) and knowledge-based (KBV) views to develop a series of propositions linking KM capability to strategic and operational supply chain sustainability and competiveness and test their veracity with practicing managers (n?=?275). We offer a systematic analysis of KM’s role in the development of SSCM. The findings confirm the credibility of the theoretical propositions and identify how different KM processes specifically facilitate strategic or operational development of SSCs. We provide researchers with a framework to guide future research at the KM/TBL nexus.     

Incorporating cost and environmental factors in quality function deployment using data envelopment analysis

Quality function deployment (QFD) is an important tool available to organizations for efficient product design and development. Traditionally, QFD rates the design requirements (DRs) with respect to customer needs, and aggregates the ratings to get relative importance scores of DRs. An increasing number of studies stress on the need to incorporate additional factors, such as cost and environmental impact, while calculating the relative importance of DRs. However, there is a paucity of methodologies for deriving the relative importance of DRs when several additional factors are considered. In this paper, data envelopment analysis (DEA) is suggested for the purpose. It is proved that the relative importance values computed by DEA coincide with traditional QFD calculations when only the ratings of DRs with respect to customer needs are considered, and when only one additional factor, namely cost, is considered. DEA provides a general framework facilitating QFD computations when more factors need to be considered. The calculations are explained using a step-by-step procedure and illustrations. The proposed QFD–DEA methodology is applied to the design of security fasteners for a Chinese company. Though traditional QFD calculations consider the ratings as cardinal numbers, DEA has the flexibility to treat the ratings as qualitative variables. This aspect is illustrated in a separate section.     

A test for randomness of the environments in a branching process

This paper discusses an approximate score test for testing randomness of environments in a branching process without observing the environments. Using an appropriate martingale central limit theorem the asymptotic null distribution of test statistic is shown to be normal. When the offspring distribution is Poisson, the detail derivation of asymptotic distribution of the test statistic is presented.     

A study of the properties of Gaussian mixture model for stable isotope standard quantification in MALDI-TOF MS

The quantification of peptides in Matrix assisted laser desorption/ionization time-of-flight mass spectrum analysis coupled with stable isotope standards has been used to quantify native peptides under many experimental conditions. This approach has difficulties quantifying samples containing peptides with ion currents in overlapping (convolved) spectra. In a previous article we proposed a reparametrized Gaussian mixture model based on the known characteristics of the peptides that could also accommodate overlapping spectra. We demonstrated the application of our model in a series of single and overlapping peptides quantification experiments. Here, we focus solely on studying the properties of our approach and examine the characteristics of the GMM approach in convolved peptides using simulated spectra and provide a method for simulating these spectra.     

Integer autoregressive models with structural breaks

Even though integer-valued time series are common in practice, the methods for their analysis have been developed only in recent past. Several models for stationary processes with discrete marginal distributions have been proposed in the literature. Such processes assume the parameters of the model to remain constant throughout the time period. However, this need not be true in practice. In this paper, we introduce non-stationary integer-valued autoregressive (INAR) models with structural breaks to model a situation, where the parameters of the INAR process do not remain constant over time. Such models are useful while modelling count data time series with structural breaks. The Bayesian and Markov Chain Monte Carlo (MCMC) procedures for the estimation of the parameters and break points of such models are discussed. We illustrate the model and estimation procedure with the help of a simulation study. The proposed model is applied to the two real biometrical data sets.     

Easy Implementation of Writing in Introductory Statistics Courses

In the past decade there has been a substantial increase in the number of introductory statistics courses taught at the undergraduate level. Many have argued successfully for the extensive use of writing in such courses in an attempt to highlight the interdisciplinary role of statistics and acknowledge that a good statistician must also be good at summarizing his or her analyses to nonstatisticians. This point was made by Radke-Sharpe, who went on to add that incorporating writing demands time, energy, and creativity, but that it is usually well worth the effort. This article discusses the efforts made by the authors to include writing in their courses, and some of the techniques that made the writing process painless and productive for both students and faculty.