Addressing the problem of missing data in decision tree modeling

Tree-based models (TBMs) can substitute missing data using the surrogate approach (SUR). The aim of this study is to compare the performance of statistical imputation against the performance of SUR in TBMs. Employing empirical data, a TBM was constructed. Thereafter, 10%, 20%, and 40% of variable values appeared as the first split was deleted, and imputed with and without the use of outcome variables in the imputation model (IMP? and IMP+). This was repeated one thousand times. Absolute relative bias above 0.10 was defined as sever (SARB). Subsequently, in a series of simulations, the following parameters were changed: the degree of correlation among variables, the number of variables truly associated with the outcome, and the missing rate. At a 10% missing rate, the proportion of times SARB was observed in either SUR or IMP? was two times higher than in IMP+ (28% versus 13%). When the missing rate was increased to 20%, all these proportions were approximately doubled. Irrespective of the missing rate, IMP+ was about 65% less likely to produce SARB than SUR. Results of IMP? and SUR were comparable up to a 20% missing rate. At a high missing rate, IMP? was 76% more likely to provide SARB estimates. Statistical imputation of missing data and the use of outcome variable in the imputation model is recommended, even in the content of TBM.     

Attribute-variable Inspection Policy for Lots Using Resampling Based on EWMA

A new mixed sampling plan which is a combination of the attribute single sampling plan and variables resampling scheme based on EWMA statistic is proposed in this paper. The operating characteristic function of the proposed plan is derived and the plan parameters are determined such that the probability of acceptance of good lot is larger than the specified producer's confidence level and the bad lot acceptance probability is smaller than the consumer's confidence level. The efficiency and the advantages of the proposed plan are discussed over the existing attribute sampling plan. The extensive tables are provided for industrial applications. The use of tables is discussed with the help of a real-time industrial example.     

Competencies of disabled entrepreneurs in Iran: implications for learning and development

This qualitative research set out to explore competencies of disabled entrepreneurs by presenting their lived experiences in developing their capabilities to create and manage their own business. The research also aimed to identify the dimensions and components of entrepreneurial competencies of disabled entrepreneurs. The participants were 16 entrepreneurs with physical and mobility disabilities, four educational managers of disabled vocational education and rehabilitation centers, and four entrepreneurship academics. Our findings suggested that the disabled entrepreneurs possess specific personal and functional entrepreneurial competencies. Personal competencies include attitudinal competencies, entrepreneurial self-efficacy and entrepreneurship learning self-efficacy. Functional competencies encompass entrepreneurial competencies, commitment and social competencies.     

Comparisons of decision tree methods using water data

This article demonstrates the application of classification trees (decision trees), logistic regression (LR), and linear discriminant function (LDR) to classify data of water quality (i.e., whether the water is fit for drinking on not fit for drinking). The data on water quality were obtained from Pakistan Council of Research in Water Resources (PCRWR) for two cities of Pakistan—one representing industrial environment (Sialkot) and the other one representing non-industrial environment (Narowal). To classify data on water quality, three statistical tools were employed—the Decision Tree methodology using Gini Index, LR, and LDA—using R software library. The results obtained by the said three techniques were compared using misclassification rates (a model with minimum value of misclassification rate is better). It was witnessed that LR performed well than the other two techniques while the Decision trees and LDA performed equally well. But for illustration purposes decision trees technique is comparatively easy to draw and interpret.     

Design of a sign chart using a new EWMA statistic

Abstract

In this article, a new non parametric control chart based on the modified or controlled exponentially weighted moving average (EWMA) statistic is developed to monitor the process deviation from the target value. The proposed control chart is evaluated for different values of design parameters using the average run length as a performance criterion under various sample sizes. The proposed chart is compared with the existing non parametric EWMA sign control chart. It is observed that the proposed chart is better than the existing EWMA sign control chart in terms of run length characteristics. An empirical example is provided for the practical implementation of the proposed chart.     

Designing a control chart of extended EWMA statistic based on multiple dependent state sampling

In this paper, we presented a memory type control chart (CC) based on multiple dependent state (MDS) sampling to pinpoint the slight variation in the process mean for the quality trait of normal distribution (ND). Two pairs of control limits denominated as internal and external control limits are derived using under control mean and variance. The essential steps are taken to get the value of average run length (ARL) for stable and disturb process. Various tables of ARLs are erected using different smoothing constants, shifts and MDS parameter. Comparisons are established to assess the effectiveness of initiated CC with the various existing CC in term of ARL. It has been ascertained that offered CC manifest the best performance in searching out the diminutive changes in the process mean. Two examples, one is based on simulation study and other is related to real-life data, have been discussed for its practical purpose.KEYWORDS: Multiple dependent state, normal distribution, smoothing constants, control chart     

Transport Mode Selection for Toxic Gases: Rail or Road?

A significant majority of hazardous materials (hazmat) shipments are moved via the highway and railroad networks, wherein the latter mode is generally preferred for long distances. Although the characteristics of highway transportation make trucks the most dominant surface transportation mode, should it be preferred for hazmat whose accidental release can cause catastrophic consequences? We answer this question by first developing a novel and comprehensive assessment methodology—which incorporates the sequence of events leading to hazmat release from the derailed railcars and the resulting consequence—to measure rail transport risk, and second making use of the proposed assessment methodology to analyze hazmat transport risk resulting from meeting the demand for chlorine and ammonia in six distinct corridors in North America. We demonstrate that rail transport will reduce risk, irrespective of the risk measure and the transport corridor, and that every attempt must be made to use railroads to transport these shipments.     

Efficient Estimation of the PDF and the CDF of the Exponentiated Gumbel Distribution

The exponentiated Gumbel model has been shown to be useful in climate modeling including global warming problem, flood frequency analysis, offshore modeling, rainfall modeling, and wind speed modeling. Here, we consider estimation of the probability density function (PDF) and the cumulative distribution function (CDF) of the exponentiated Gumbel distribution. The following estimators are considered: uniformly minimum variance unbiased (UMVU) estimator, maximum likelihood (ML) estimator, percentile (PC) estimator, least-square (LS) estimator, and weighted least-square (WLS) estimator. Analytical expressions are derived for the bias and the mean squared error. Simulation studies and real data applications show that the ML estimator performs better than others.     

Conditional residual lifetimes of coherent systems under double monitoring

In this paper, we obtain a mixture representation for the reliability function of the conditional residual lifetime of a coherent system with n independent and identically distributed (i.i.d.) components under double monitoring. We suppose that at time t₁, j components have failed while at time t₂ the system is still alive. Based on these mixture representation, we then study stochastic comparisons of the conditional residual lifetimes of two coherent systems with independent and identical components.     

Cross‐Cultural Measurement Invariance of Adolescent Self‐Report on the Pediatric Quality of Life Inventory™ 4.0

This study evaluated the cross‐cultural measurement invariance of the Pediatric Quality of Life Inventory version 4.0 (PedsQL^?) among adolescents sampled from Bulgaria, Croatia, India, Indonesia, Nigeria, Serbia, and Turkey. The multiple‐indicator multiple‐cause (MIMIC) model was used, which allowed controlling of demographic variables (i.e., age, gender, and socioeconomic status). Significant effects of country on scores within the PedsQL^? domains were observed, with up to 17 items showing differential item functioning (DIF) across the countries. We did not find support for cross‐cultural measurement invariance hypotheses for scores on the PedsQL^? adolescent self‐report in this study. Researchers should use caution in making cross‐cultural quality of life comparisons while using the PedsQL.