A novel approach based on multiple correspondence analysis for monitoring social networks with categorical attributed data

In in most cases, the distribution of communications is unknown and one may summarize social network communications with categorical attributes in a contingency table. Due to the categorical nature of the data and a large number of features, there are many parameters to be considered and estimated in the model. Hence, the accuracy of estimators decreases. To overcome the problem of high dimensionality and unknown communications distribution, multiple correspondence analysis is used to reduce the number of parameters. Then the rescaled data are studied in a Dirichlet model in which the parameters should be estimated. Moreover, two control charts, Hotelling’s T² and multivariate exponentially weighted moving average (MEWMA), are developed to monitor the parameters of the Dirichlet distribution. The performance of the proposed method is evaluated through simulation studies in terms of average run length criterion. Finally, the proposed method is applied to a real case.     

Disaster Management from a POM Perspective: Mapping a New Domain

We have reviewed disaster management research papers published in major operations management, management science, operations research, supply chain management and transportation/logistics journals. In reviewing these studies, our objective is to assess and present the macro level “architectural blue print” of disaster management research with the hope that it will attract new researchers and motivate established researchers to contribute to this important field. The secondary objective is to bring this disaster research to the attention of disaster administrators so that disasters are managed more efficiently and more effectively. We have mapped the disaster management research on the following five attributes of a disaster: (1) Disaster Management Function (decision‐making process, prevention and mitigation, evacuation, humanitarian logistics, casualty management, and recovery and restoration), (2) Time of Disaster (before, during and after), (3) Type of Disaster (accidents, earthquakes, floods, hurricanes, landslides, terrorism and wildfires etc.), (4) Data Type (Field and Archival data, Real data and Hypothetical data), and (5) Data Analysis Technique (bidding models, decision analysis, expert systems, fuzzy system analysis, game theory, heuristics, mathematical programming, network flow models, queueing theory, simulation and statistical analysis). We have done cross tabulations of data among these five parameters to gain greater insights into disaster research. Recommendations for future research are provided.     

Analysis of covariance under inverse Gaussian model

This paper considers the problem of analysis of covariance (ANCOVA) under the assumption of inverse Gaussian distribution for response variable. We develop the essential methodology for estimating the model parameters via maximum likelihood method. The general form of the maximum likelihood estimator is obtained in color closed form. Adjusted treatment effects and adjusted covariate effects are given, too. We also provide the asymptotic distribution of the proposed estimators. A simulation study and a real world application are also performed to illustrate and evaluate the proposed methodology.     

Testing the equality of two independent regression models

In some situations, for example in agriculture, biology, hydrology, and psychology, researchers wish to determine whether the relationship between response variable and predictor variables differs in two populations. In other words, we are interested in comparing two regression models for two independent datasets. In this work, we will use the parametric and nonparametric methods to establish hypothesis testing for the equality of two independent regression models. Then the simulation study is provided to investigate the performance of the proposed method.     

Aging,Depression, and Wisdom: A Pilot Study of Life-Review Intervention and PTSD Treatment With Two Groups of Vietnam Veterans

Vietnam War veterans are a sometimes overlooked subgroup of the aging baby boomer generation. Forty years after the war ended, war veterans still seek out VA or Vet Center counselors to assist with traumatic stress symptoms. However, there currently are no specific age-related protocols for treating older war veterans suffering from posttraumatic stress disorder (PTSD), nor have established PTSD interventions incorporated gerontology content for these older trauma survivors. This pilot study juxtaposed life review within regular PTSD group counseling for 12 Vietnam veterans at a community-based Vet Center using a partial crossover design. The Life Review and Experiencing Form (LREF) structured the delivery of the life review component. T-tests and repeated measures ANOVA were used to examine depression and self-assessed wisdom outcomes using measures previously tested with older adults. Findings suggest that life review prior to PTSD group therapy has clinical benefits for reducing symptoms of depression and increasing self-assessed wisdom. The study illuminates the possible relationship of traumatic stress symptom effects on the natural reminiscing process for older veterans and provides insights into methods for more age-appropriate treatment for trauma survivors participating in Vet Center and VA programs nationwide.     

Outcomes of parental mental illness on children: a qualitative study from Iran

Children of parents with mental illness are a substantial, yet marginalized group. This study, as part of a more extensive research project, used grounded theory to explore the outcomes of parental mental illness on their children. Seventeen informants were interviewed at a mental hospital in the city of Qazvin, Iran. The participants were selected using purposeful and theoretical sampling. Interviews were analyzed using Strauss and Corbin's method. It was revealed that parental mental illness leads to five major outcomes that involve communication, mental, educational, economic, and extra roles factors. As such, it is suggested that these children should be considered within health care plans and that policy makers, nurses, and other health care providers use these findings for preventive and educational purposes.