“I'm Still Fighting for the Two of Us”: How Partners of UK Veterans Construct Their Experience of Living with Combat‐Related Trauma

There has been little qualitative research into the experiences of UK partners of veterans with PTSD. This study therefore aimed to explore how partners constructed their experiences of living with the condition. Fifteen female partners of male UK veterans were recruited and interviewed. Using a social constructionist thematic analysis, five themes were constructed: the women's need to subdue own emotional and behavioral responses; dilemmas about whether the veteran was unwell or ‘bad’; attempts at negotiating multiple roles; challenging the narrative of veterans as heroes; and the relational struggle with the transition to nonmilitary life. This study highlighted the importance of considering the veteran as existing within a relational and cultural context, and the need to include partners in therapeutic interventions.     

A two-stage phase II trial design utilizing both primary and secondary endpoints

Phase II trials in oncology drug development are usually conducted to perform the initial assessment of treatment activity. The common designs in this setting, for example, Simon 2-stage designs, are often developed based on testing whether a parameter of interest, usually a proportion (e.g. response rate), is less than a certain level or not. These designs usually consider only one parameter. However, sometimes we may encounter situations where we need to consider not a single parameter, but multiple parameters. This paper presents a two-stage design in which both primary and secondary endpoints are utilized in the decision rules. The family-wise Type 1 error rate and statistical power of the proposed design are investigated under a variety of situations by means of Monte-Carlo simulations.     

Three cultural models of teacher interaction valued by Mexican students at a US high school

Using students’ interviews as data source, this study explores the interactional experiences of several Mexican students at a US high school in the Midwest with their teachers and discusses how three cultural models of teacher interaction valued by the students impact their affiliation, motivation, and engagement with school. Emphasis is given to the students’ voices to explore how teachers are perceived by them. The study found that several teachers displayed negative stereotypes influenced by cultural and social biases toward Mexicans and the anti-immigrant climate in society. Insights are provided regarding the manner in which Mexican students’ teacher interaction influences their high drop out rate, their low academic achievement, and their low graduation statistics. The findings suggest that there is an urgent need to improve teachers’ cultural awareness and cultural sensitivity toward Mexican students.     

Estimation and Inference With Weak,Semi‐Strong,and Strong Identification

This paper analyzes the properties of standard estimators, tests, and confidence sets (CS's) for parameters that are unidentified or weakly identified in some parts of the parameter space. The paper also introduces methods to make the tests and CS's robust to such identification problems. The results apply to a class of extremum estimators and corresponding tests and CS's that are based on criterion functions that satisfy certain asymptotic stochastic quadratic expansions and that depend on the parameter that determines the strength of identification. This covers a class of models estimated using maximum likelihood (ML), least squares (LS), quantile, generalized method of moments, generalized empirical likelihood, minimum distance, and semi‐parametric estimators. The consistency/lack‐of‐consistency and asymptotic distributions of the estimators are established under a full range of drifting sequences of true distributions. The asymptotic sizes (in a uniform sense) of standard and identification‐robust tests and CS's are established. The results are applied to the ARMA(1, 1) time series model estimated by ML and to the nonlinear regression model estimated by LS. In companion papers, the results are applied to a number of other models.     

Using Social Media to Change the Narrative Around Chronic Illness

Chronic illness is a prevalent issue for many individuals. Various theoretical approaches have been employed in the psychotherapeutic treatment of chronic illness and the effects it has on the individual with the illness. These approaches frequently overlook the strengths of the person living with the illness as well as fail to address aspects of modern life such as social media use of the client and the influence it holds for those living with a chronic illness. This paper proposes the application of narrative therapy and social media use as a narrative therapeutic technique when treating those who suffer from chronic illness. A clinical vignette is used to illustrate possible applications of therapeutic techniques in conjunction with therapist-directed social media use. Implications for clinical practice and limitations are discussed.     

Inference in the presence of redundant moment conditions and the impact of government health expenditure on health outcomes in England

In his 1999 article with Breusch, Qian, and Wyhowski in the Journal of Econometrics, Peter Schmidt introduced the concept of “redundant” moment conditions. Such conditions arise when estimation is based on moment conditions that are valid and can be divided into two subsets: one that identifies the parameters and another that provides no further information. Their framework highlights an important concept in the moment-based estimation literature, namely, that not all valid moment conditions need be informative about the parameters of interest. In this article, we demonstrate the empirical relevance of the concept in the context of the impact of government health expenditure on health outcomes in England. Using a simulation study calibrated to this data, we perform a comparative study of the finite performance of inference procedures based on the Generalized Method of Moment (GMM) and info-metric (IM) estimators. The results indicate that the properties of GMM procedures deteriorate as the number of redundant moment conditions increases; in contrast, the IM methods provide reliable point estimators, but the performance of associated inference techniques based on first order asymptotic theory, such as confidence intervals and overidentifying restriction tests, deteriorates as the number of redundant moment conditions increases. However, for IM methods, it is shown that bootstrap procedures can provide reliable inferences; we illustrate such methods when analysing the impact of government health expenditure on health outcomes in England.     

Conditional Linear Combination Tests for Weakly Identified Models

We introduce the class of conditional linear combination tests, which reject null hypotheses concerning model parameters when a data‐dependent convex combination of two identification‐robust statistics is large. These tests control size under weak identification and have a number of optimality properties in a conditional problem. We show that the conditional likelihood ratio test of Moreira, 2003 is a conditional linear combination test in models with one endogenous regressor, and that the class of conditional linear combination tests is equivalent to a class of quasi‐conditional likelihood ratio tests. We suggest using minimax regret conditional linear combination tests and propose a computationally tractable class of tests that plug in an estimator for a nuisance parameter. These plug‐in tests perform well in simulation and have optimal power in many strongly identified models, thus allowing powerful identification‐robust inference in a wide range of linear and nonlinear models without sacrificing efficiency if identification is strong.     

A Swiss‐Army Knife? A Critical Assessment of the Extractive Industries Transparency Initiative (EITI) in Ghana

Within the current global atmosphere where a universally accepted police force is nonexistent, there are several voluntary norms and codes of conduct that exist to guide how corporations behave worldwide. These have come as a result of many years of poor performance in the areas of social, financial, and environmental responsibility. Such norms are expected to prescribe and proscribe certain types of corporate behavior but when one examines the reality on the ground, the story is not that straightforward. This article assesses the effectiveness of the Extractive Industries Transparency Initiative (EITI) in the Ghanaian context with a focus on the mining sector. Based on primary qualitative data the argument is that even though the EITI is performing some function, it has ways to go before it can become an across‐the‐board viable tool for transparency and proper accountability. Five prevailing weaknesses are discussed to underscore this case.     

Models of cognition and affect in perceptions of well-being

How do people arrive at assessments of their own life quality? A series of models was developed to provide an interpretation of the way the factors of cognition and affect operate along with evaluations of specific life concerns (domains) in the perception of well-being. Following previous research, cognition was defined operationally as a factor which accounts for the covariance among a set of assessments of life-as-a-whole after affect, as measured by Bradburn's scales, is partialled out and after allowance is made for the presence of correlated measurement errors. It was found that loadings on the cognitive factor, and hence the interpretation of this factor, changed little despite quite large changes in the models. Moreover, in all major comparisons, models that contained the cognitive factor fitted the data better than models that did not. Models that included affect as the only variable intervening between the domains and the life-as-a-whole factor led to results that were intuitively difficult to accept. In the preferred model both affect and cognition were positioned as intervening variables. In this model it was found that the domain evaluations had no direct impact on life-as-a-whole assessments — the contribution of the domains was indirect by way of their association with cognition and affect. It was hypothesised that associated with each domain was a domain-specific element of affect and a domain-specific element of cognition. The linear additive relation found by previous researchers between domain evaluations and life-as-a-whole assessments would then be explainable as a statistical result arising from the summing of the domain-specific elements of affect and cognition.     

The use of zip coded population data in social area studies of service utilization

Social area analysis (SAA) is a well-established methodology for geographically based analysis of service delivery and other health related outcome measures. However, SAA has been limited in application by the complexities of computerized geocoding and difficulties in obtaining appropriate measures of community characteristics. In this paper we demonstrate that these problems can be overcome by employing zip code as well as the unit of analysis for SAA and obtaining commercially available measures of community characteristics. Regression analyses, using New York City zip code populations as the unit of observation were used to illustrate the role of epidemiologic risk factors in predicting rates of inpatient discharge and ambulatory care visits.