The Impact of Organizational Change on Employee Turnover Intention: Does Stress Play a Mediating Role?

This study examined the relationship between change interventions and employee turnover intention to see if change interventions lead to increased employee turnover intention. Moreover, the mediating role of employee stress was tested. Data were collected from 162 respondents working at various administrative positions in a large public organization. The results indicate that employee turnover intention is positively correlated to human process, techno structural, human resources, and strategic interventions. Limitations and direction for future research are provided.     

On Using Negative Binomial Distribution as a Randomization Device in Sensitive Surveys

In this article, an interesting improvement of some recent randomized response techniques has been proposed. The proposed randomized response technique applies Negative Binomial distribution to obtain data from respondents. An unbiased estimator of proportion of a sensitive attribute has been suggested and it is shown, numerically, that the new estimator performs better than the recent estimators while doing a sensitive survey. It is also established that the proposed estimator is unconditionally better than that of the estimator based on using the geometric distribution.     

Predictive Inference from a Two-Parameter Rayleigh Life Model Given a Doubly Censored Sample

This article is concerned with making predictive inference on the basis of a doubly censored sample from a two-parameter Rayleigh life model. We derive the predictive distributions for a single future response, the ith future response, and several future responses. We use the Bayesian approach in conjunction with an improper flat prior for the location parameter and an independent proper conjugate prior for the scale parameter to derive the predictive distributions. We conclude with a numerical example in which the effect of the hyperparameters on the mean and standard deviation of the predictive density is assessed.     

Improved Predictive Inference for Responses Based on Location Parameter Median from the Rayleigh Model Given a Doubly Censored Sample

The purpose of this article is to investigate the predictive inference for responses from the location parameter mean as well as from the median given a doubly censored sample from the two-parameter Rayleigh model. The predictive results by Khan et al. (2010 Khan , H. M. R. , Provost , S. B. , Ashima , S. ( 2010 ). Predictive Inference from a Two-Parameter Rayleigh Life Model Given a Doubly Censored Sample . Commun. Statist. Theor. Meth. 39 ( 7 ): 1237 – 1246 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) are used to obtain the predictive inference for responses from the median, where Khan et al. (2010 Khan , H. M. R. , Provost , S. B. , Ashima , S. ( 2010 ). Predictive Inference from a Two-Parameter Rayleigh Life Model Given a Doubly Censored Sample . Commun. Statist. Theor. Meth. 39 ( 7 ): 1237 – 1246 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) obtained the future estimates from the mean. A numerical example representing 66 liver cancer patients is used for predictive analysis. It is concluded that the predictive inference from the median gives precise results as compared with the location parameter mean.     

Are rural–urban migrants living in urban slums more vulnerable in terms of housing,health knowledge,smoking, mental health and general health?

The magnitude of rural–urban migration in Bangladesh is increasing. Rapid urbanisation and a growing number of slums (dominated by migrants) pose many challenges to health. To our knowledge, studies regarding internal migration and health are scarce and results are mixed. Therefore, we compared several aspects, namely: housing, health knowledge, smoking, mental and general health, for three groups of migrants, designated urban natives/urban to urban migrants (UN/UU), rural to urban migrants (RU) and rural natives/rural to rural migrants (RN/RR). Results based on a sample of 5,136 adults indicated that the majority of respondents were less than 50 years old, female, married and uneducated. The percentages of UN/UU, RU and RN/RR migrants were 9.6, 69.2 and 21.3, respectively. As both bivariable and multivariable analyses indicated greater vulnerability among RU migrants in terms of the above‐mentioned aspects, this particular group deserves more attention from policy‐makers and other stakeholders. Some implications are also discussed. Key Practitioner Message: ● This study provides information regarding internal migration and explains push–pull factors in Bangladesh; ● It provides evidence regarding greater vulnerability in terms of health and other determinants among rural–urban migrants living in Dhaka slums; ● Lastly, the study justifies the importance of intervention strategies targeting poor migrants in urban slums in developing countries.     

Determining the optimal allocation of testing resource for modular software system using dynamic programming

Abstract

Reliability is a major concern in the process of software development because unreliable software can cause failure in the computer system that can be hazardous. A way to enhance the reliability of software is to detect and remove the faults during the testing phase, which begins with module testing wherein modules are tested independently to remove a substantial number of faults within a limited resource. Therefore, the available resource must be allocated among the modules in such a way that the number of faults is removed as much as possible from each of the modules to achieve higher software reliability. In this article, we discuss the problem of optimal resource allocation of the testing resource for a modular software system, which maximizes the number of faults removed subject to the conditions that the amount of testing-effort is fixed, a certain percentage of faults is to be removed and a desired level of reliability is to be achieved. The problem is formulated as a non linear programming problem (NLPP), which is modeled by the inflection S-shaped software reliability growth models (SRGM) based on a non homogeneous Poisson process (NHPP) which incorporates the exponentiated Weibull (EW) testing-effort functions. A solution procedure is then developed using a dynamic programming technique to solve the NLPP. Furthermore, three special cases of optimum resource allocations are also discussed. Finally, numerical examples using three sets of software failure data are presented to illustrate the procedure developed and to validate the performance of the strategies proposed in this article. Experimental results indicate that the proposed strategies may be helpful to software project managers for making the best decisions in allocating the testing resource. In addition, the results are compared with those of Kapur et al. (2004), Huang and Lyu (2005), and Jha et al. (2010) that are available in the literature to deal the similar problems addressed in this article. It reveals that the proposed dynamic programming method for the testing-resource allocation problem yields a gain in efficiency over other methods.     

Structural inference of the parameters of the heteroscedastic simultaneous equation model

The structural approach of inference for the parameters of a simultaneous equation model with heteroscedastic error variance is investigated in this paper. The joint and the marginal structural distributions for the coefficients of the exogenous variables and the scale parameters of the error variables, and the marginal likelihood function of the coefficients of the endogenous variables have been derived. The estimates are directly obtainable from the structural distribution and the marginal likelihood function of the parameters. The marginal distribution of a subset of coefficients of exogenous variables provides the basis for making inference for a particular subset of parameter of interest.     

Maximum likelihood estimation of variance components of heteroscedastic random anova model

the estimation of variance components of heteroscedastic random model is discussed in this paper. Maximum Likelihood (ML) is described for one-way heteroscedastic random models. The proportionality condition that cell variance is proportional to the cell sample size, is used to eliminate the efffect of heteroscedasticity. The algebraic expressions of the estimators are obtained for the model. It is seen that the algebraic expressions of the estimators depend mainly on the inverse of the variance-covariance matrix of the observation vector. So, the variance-covariance matrix is obtained and the formulae for the inversions are given. A Monte Carlo study is conducted. Five different variance patterns with different numbers of cells are considered in this study. For each variance pattern, 1000 Monte Carlo samples are drawn. Then the Monte Carlo biases and Monte Carlo MSE’s of the estimators of variance components are calculated. In respect of both bias and MSE, the Maximum Likelihood (ML) estimators of variance components are found to be sufficiently good.     

Bayesian quantile regression for ordinal longitudinal data

Since the pioneering work by Koenker and Bassett [27], quantile regression models and its applications have become increasingly popular and important for research in many areas. In this paper, a random effects ordinal quantile regression model is proposed for analysis of longitudinal data with ordinal outcome of interest. An efficient Gibbs sampling algorithm was derived for fitting the model to the data based on a location-scale mixture representation of the skewed double-exponential distribution. The proposed approach is illustrated using simulated data and a real data example. This is the first work to discuss quantile regression for analysis of longitudinal data with ordinal outcome.     

Sexual and reproductive health knowledge and information-seeking behavior among middle eastern female university students: a systematic review

Objectives: The objective of this study was to collate the level of sexual and reproductive health knowledge, awareness, attitudes, and behavior among female university students, in addition to identifying their sources of information in Middle Eastern and North African countries. Methods: A systematic review was conducted with a search in Medline, EMBASE, Web of Knowledge, PsycINFO, and CINAHL from inception to February 2013. Included were studies in any language describing sexual and reproductive health knowledge and attitudes among female university students. Results: Nine studies were included, and all were cross-sectional surveys. There was a general lack of knowledge of sexual and reproductive health. The highest knowledge levels reported were for HIV. Conclusions: There are deficiencies in sexual and reproductive health knowledge and behavior in Middle Eastern and North African countries. Studies are needed to evaluate how to provide culturally sensitive sexual and reproductive health information.