Entropy-Based Moment Selection in the Presence of Weak Identification

Hall et al. (2007 Hall , A. R. , Inoue , A. , Jana , K. , Shin , C. (2007). Information in generalized method of moments estimation and entropy based moment selection. Journal of Econometrics 138:488–512.[Crossref] , [Google Scholar]) propose a method for moment selection based on an information criterion that is a function of the entropy of the limiting distribution of the Generalized Method of Moments (GMM) estimator. They establish the consistency of the method subject to certain conditions that include the identification of the parameter vector by at least one of the moment conditions being considered. In this article, we examine the limiting behavior of this moment selection method when the parameter vector is weakly identified by all the moment conditions being considered. It is shown that the selected moment condition is random and hence not consistent in any meaningful sense. As a result, we propose a two-step procedure for moment selection in which identification is first tested using a statistic proposed by Stock and Yogo (2003 Stock , J. H. , Yogo , M. ( 2003 ). Testing for weak instruments in linear IV regression . Discussion paper, Kennedy School of Government, Harvard University, Cambridge, MA . [Google Scholar]) and then only if this statistic indicates identification does the researcher proceed to the second step in which the aforementioned information criterion is used to select moments. The properties of this two-step procedure are contrasted with those of strategies based on either using all available moments or using the information criterion without the identification pre-test. The performances of these strategies are compared via an evaluation of the finite sample behavior of various methods for inference about the parameter vector. The inference methods considered are based on the Wald statistic, Anderson and Rubin's (1949 Anderson , T. W. , Rubin , H. ( 1949 ). Estimation of the parameters of a single equation in a complete system of stochastic equations . Annals of Mathematical Statistics 20 : 46 – 63 .[Crossref] , [Google Scholar]) statistic, Kleibergen (2002 Kleibergen , F. ( 2002 ). Pivotal statistics for testing structural parameters in instrumenatl variables regression . Econometrica 70 : 1781 – 1803 .[Crossref], [Web of Science ®] , [Google Scholar]) K statistic, and combinations thereof in which the choice is based on the outcome of the test for weak identification.     

Bootstrap-Based T 2 Multivariate Control Charts

Control charts have been used effectively for years to monitor processes and detect abnormal behaviors. However, most control charts require a specific distribution to establish their control limits. The bootstrap method is a nonparametric technique that does not rely on the assumption of a parametric distribution of the observed data. Although the bootstrap technique has been used to develop univariate control charts to monitor a single process, no effort has been made to integrate the effectiveness of the bootstrap technique with multivariate control charts. In the present study, we propose a bootstrap-based multivariate T ² control chart that can efficiently monitor a process when the distribution of observed data is nonnormal or unknown. A simulation study was conducted to evaluate the performance of the proposed control chart and compare it with a traditional Hotelling's T ² control chart and the kernel density estimation (KDE)-based T ² control chart. The results showed that the proposed chart performed better than the traditional T ² control chart and performed comparably with the KDE-based T ² control chart. Furthermore, we present a case study to demonstrate the applicability of the proposed control chart to real situations.     

Aftermath of tragic events: the development and use of community support meetings on a university campus

Colleges and universities need to be prepared to address the psychological impact of tragedies on their campuses. In this article, the author describes the development and successful implementation of campus postvention services in the aftermath of college student deaths by suicide as well as by natural and accidental causes. The program has been well received and has gone a long way toward helping the campus community come together and heal after these types of tragedies. College officials adapted the program to address issues related to troubling national and international events as well local incidents, such as suicide attempts and students' loss of housing through fires. The author provides specific instructions so that readers can replicate the program on their own campuses, and additional materials are available upon request.     

Characteristics of social smoking among college students

Social smoking is a newly identified phenomenon in the young adult population that is poorly understood. We investigated differences in social smoking (smoking most commonly while partying or socializing) and other smoking within a convenience sample of college smokers (n = 351) from a large midwestern university. Results revealed that 70% of 351 current (past 30-day) smokers reported social smoking. No significant difference was found in motivation to quit between smoking groups. However, a significant difference was found between groups in confidence to quit, the number of days smoked, and the number of cigarettes smoked on those days. More social smokers than expected did not perceive themselves as smokers. Logistic regression analysis revealed that lower physical and psychological dependence and higher social support scores predicted social smoking.     

Factors that influence battered women to leave their abusive relationships

This study examines factors associated with leaving an abusive relationship, including relationship characteristics, external support, and health status of the abused subjects. The subjects included 448 Seattle women whose abuse resulted in police involvement or filing for a civil protection order against their male partner. Women were followed longitudinally for 9 months. Stepwise logistic regression analyses assessed factors independently predictive of leave taking. Predictors of leaving the abusive relationship were young age, leaving the relationship previously, and having a protection order, an abuse-related physician visit, and a high score of psychological vulnerability to abuse. Seeking but not receiving external support was negatively associated with leave taking.     

The Four Es of Problem Gambling: A Psychological Measure of Risk

A focus group of Reno area Gamblers Anonymous members identified four psychological traits contributing to risk for problem gambling, including: Escape, Esteem, Excess and Excitement. A panel of four experts authored 240 Likert-type items to measure these traits. By design, none of the items explicitly referred to gambling activities. Study 1 narrowed the field of useful items by employing a quasi-experimental design which compared the answers of Reno area Gamblers Anonymous members (N = 39) to a control sample (N = 34). Study 2 submitted successful items, plus new items authored with the knowledge gained from Study 1, to validation in a random sample telephone survey across Queensland, Australia (N=2577). The final 40 item Four Es scale (4Es) was reliable (α=.90); predicted gambling problems as measured by the Canadian Problem Gambling Index of Severity (PGSI, Ferris & Wynne (2001). The Canadian Problem Gambling Index: Final Report: Canadian Centre on Substance Abuse); and distinguished problem gamblers from persons with alcohol abuse problems. The new scale can provide a basis for further study in harm minimization, treatment, and theory development.     

Effective strategies for socio-educational intervention during the process of transition to adult life of unaccompanied minors from Africa

The arrival of unaccompanied minors from Africa in Spanish territory has been a constant since the last decade of the twentieth century. This migratory phenomenon has forced the child welfare system to attend to thousands of migrant children. The transition to adult life is a decisive stage in overcoming the situation of social exclusion. This research aims to analyse which socio-educational intervention strategies are effective during the process of transition to independent living with unaccompanied minors of African origin. We designed a qualitative research according to the grounded theory, which we divided into two phases. Twenty-nine young people (26 men and 3 women) participated. In phase 1, we performed two focus groups (N = 11), and in phase 2, we conducted longitudinal follow-ups (N = 18) for 24 months through 180 interviews. The results indicate the effectiveness of designing socio-educational accompaniment, prioritizing spaces of trust from which to attain the goals of emancipation. Young people consider effective those strategies that favour their knowledge of the social, labour and legal reality of the host society, designed considering each minor's individualized situation. We concluded that professional involvement acts as a buffer, reducing the bureaucratic obstacles implemented by the Spanish government.     

Do Interactions between Unemployment Insurance and Sickness Insurance Affect Transitions to Employment?

Previous research suggests that there are substantial interactions between the unemployment and sickness insurance in Sweden. Moral hazard arises in the interplay between these insurance systems, as by reporting sick an unemployed person can postpone unemployment insurance expiration and sometimes receive considerably higher benefits. I examine whether these interactions affect the transition rate to employment. To do this I use a reform that greatly reduced the incentives to transfer to sickness benefits. Although there is evidence that this reform effectively lowered the incidence of sick reports among the unemployed, I do not find that the reduced sick report rate in turn affected the transition rate to employment.     

Defining estimands for efficacy assessment in single arm phase 1b or phase 2 clinical trials in oncology early development

The addendum of the ICH E9 guideline on the statistical principles for clinical trials introduced the estimand framework. The framework is designed to strengthen the dialog between different stakeholders, to introduce greater clarity in the clinical trial objectives and to provide alignment between the estimand and statistical analysis. Estimand framework related publications thus far have mainly focused on randomized clinical trials. The intention of the Early Development Estimand Nexus (EDEN), a task force of the cross-industry Oncology Estimand Working Group ( www.oncoestimand.org ), is to apply it to single arms Phase 1b or Phase 2 trials designed to detect a treatment-related efficacy signal, typically measured by objective response rate. Key recommendations regarding the estimand attributes include that in a single arm early clinical trial, the treatment attribute should start when the first dose is received by the participant. Focusing on the estimation of an absolute effect, the population-level summary measure should reflect only the property used for the estimation. Another major component introduced in the ICH E9 addendum is the definition of intercurrent events and the associated possible ways to handle them. Different strategies reflect different clinical questions of interest that can be answered based on the journeys an individual subject can take during a trial. We provide detailed strategy recommendations for intercurrent events typically seen in early-stage oncology. We highlight where implicit assumptions should be made transparent as whenever follow-up is suspended, a while-on-treatment strategy is implied.     

Inference in Arch and Garch Models with Heavy–Tailed Errors

ARCH and GARCH models directly address the dependency of conditional second moments, and have proved particularly valuable in modelling processes where a relatively large degree of fluctuation is present. These include financial time series, which can be particularly heavy tailed. However, little is known about properties of ARCH or GARCH models in the heavy–tailed setting, and no methods are available for approximating the distributions of parameter estimators there. In this paper we show that, for heavy–tailed errors, the asymptotic distributions of quasi–maximum likelihood parameter estimators in ARCH and GARCH models are nonnormal, and are particularly difficult to estimate directly using standard parametric methods. Standard bootstrap methods also fail to produce consistent estimators. To overcome these problems we develop percentile–t, subsample bootstrap approximations to estimator distributions. Studentizing is employed to approximate scale, and the subsample bootstrap is used to estimate shape. The good performance of this approach is demonstrated both theoretically and numerically.