Health Risk,Inequality Indexes,and Environmental Justice

Inequality indexes have long been used to analyze distributions of income. Studies have recently begun to use these tools to evaluate the equity of distributions of environmental harm. In response, issues have been raised regarding the appropriateness of using income-based measures in the context of undesirable outcomes. We begin from first principles, identifying a theoretical preference structure under which income-based tools can be appropriate for ranking distributions of “bads.” While some critiques of existing applications are valid, they are not a justification for rejecting the approach altogether. Instead, we show how standard income-based measures can be adjusted to accommodate bad outcomes. Rather than inequality indexes, we argue that equally distributed equivalents (EDEs) are well-suited for this purpose since they account for levels and dispersion of outcome distributions. The Kolm–Pollak EDE is particularly useful, having the advantage of consistently evaluating both bads and their complementary goods (e.g., mortality risk and survival probability). As an illustration, we show how these tools can inform an environmental justice analysis of a proposed Environmental Protection Agency (EPA) rule addressing indoor air pollution.     

Temporal Disaggregation: Methods,Information Loss,and Diagnostics

This research provides a generalized framework to disaggregate lower-frequency time series and evaluate the disaggregation performance. The proposed framework combines two models in separate stages: a linear regression model to exploit related independent variables in the first stage and a state–space model to disaggregate the residual from the regression in the second stage. For the purpose of providing a set of practical criteria for assessing the disaggregation performance, we measure the information loss that occurs during temporal aggregation while examining what effects take place when aggregating data. To validate the proposed framework, we implement Monte Carlo simulations and provide two empirical studies. Supplementary materials for this article are available online.     

Trustworthiness in evaluation practice: an emphasis on the relational

As canons for trustworthiness developed explicitly in the discourse of qualitative inquiry, the emphasis was on procedural matters rather than fundamentally relational ones. A nod was made to the relational in such strategies as “member checks” but the issues of how the evaluator actually relates to participants and to the larger communities of practice and discourse—matters subsumed under moral principles and ethical standards—were often marginalized. This chapter posits that the first consideration in designing and conducting rigorous evaluation inquiry, and in critiquing the results of any research, should be the study's trustworthiness. Judging a study's trustworthiness, however, should focus on much more than procedural matters; it should also rely on moral principles and ethical standards which specifically address how we relate to an evaluation's participants. Central to these considerations are cross-cultural sensibilities about the nuanced meanings associated with any principles and standards. The chapter provides a theoretical framework for this position and offers two illustrative examples in the form of dialogues.     

Examining the correlates of engagement and disengagement coping among help-seeking battered women

This study examined several potential correlates of engagement and disengagement coping, including abuse-related factors, socioeconomic and social coping resources, and childhood trauma variables among a sample of battered women (N = 388). Relationship abuse frequency, particularly psychological aggression, and peritraumatic dissociation were the strongest positive predictors of the use of disengagement coping. Social coping resources, including tangible support and appraisals of social support and belonging, were associated with higher engagement coping and lower disengagement coping. A positive association was also found between interparental domestic violence and disengagement coping, and negative associations were found between both childhood physical and sexual abuse and engagement coping. Results suggest that coping strategies used by battered women are multidetermined and deserve further exploration.     

The life-course origins of mastery among older people

In this article, we aim to identify the sources of mastery--the understanding that individuals hold about their ability to control the circumstances of their lives. The sample for our inquiry was drawn from the Medicare beneficiary files of people 65 and older living in Washington, DC, and two adjoining Maryland counties. We find that past circumstances, particularly those reflecting status attainment and early exposure to intractable hardships, converge with stressors experienced in late life to influence elders' level of mastery. The impact of past conditions, however, does not necessarily directly affect the current mastery of older people. Instead, the effect of prior experiences on current mastery is mediated by what we refer to as life-course mastery: one's belief that one has directed and managed the trajectories that connect one's past to the present. Our analyses show that life-course mastery largely serves as the mediating channel through which individuals connect their past to their present.     

The effect of a novel ADL-based training program on performance of activities of daily living and physical fitness

The purpose of this study was to determine the degree to which a novel training program based on activities of daily living (ADL) would affect performance of ADLs, as well as the fitness of older adults. Fourteen individuals (mean age 82 years) took part in a 10-week control period followed by a 10-week ADL-based training program. Pre- and posttests included the Physical Performance Test (PPT), the Physical Functional Performance-10 (PFP-10), and the Senior Fitness Test (SFT). After the training period, improvements ranging from 7% to 33% (p<.05) were seen on the PPT and PFP-10 and on three items of the SFT. After conversion to standard scores, the magnitude of change in the PPT and the PFP10 was significantly greater (p<.05) than the magnitude of change in the SFT. These data support the idea that this novel ADL-based training program was able to facilitate improved performance of ADLs, as well as select measures of fitness among older adults.     

Multivariate process dispersion monitoring without subgrouping

The memory-type adaptive and non-adaptive control charts are among the best control charts for detecting small-to-moderate changes in the process parameter(s). In this paper, we propose the Crosier CUSUM (CCUSUM), EWMA, adaptive CCUSUM (ACCUSUM) and adaptive EWMA (AEWMA) charts for efficiently monitoring the changes in the covariance matrix of a multivariate normal process without subgrouping. Using extensive Monte Carlo simulations, the length characteristics of these control charts are computed. It turns out that the ACCUSUM and AEWMA charts perform uniformly and substantially better than the CCUSUM and EWMA charts when detecting a range of shift sizes in the covariance matrix. Moreover, the AEWMA chart outperforms the ACCUSUM chart. A real dataset is used to explain the implementation of the proposed control charts.     

A KNOWLEDGE-BASED DSS FOR MANAGERIAL PROBLEM DIAGNOSIS

A knowledge-based system supporting managerial problem diagnosis is described. The system provides the capability to monitor values of selected variables for problem situations. When problems are located, a list of problem symptoms is delivered to a problem processor for structuring and diagnosis. Problem structuring is based on a combination of concepts from expert systems and structural modeling. User assertions about cause-effect relationships between pairs of variables are maintained in a semantic network. Problem diagnosis uses the relationships in the semantic network to construct causation trees, the branches of which represent potential explanations of the problem symptoms. Mathematical models are constructed based on causation-tree branches, and values from the data base are used to test whether the model confirms the diagnosis. If so, the source of the problem has been located and it is then up to the user to resolve the problem. If the model fails to explain the problem, the model apparently is deficient and the user may perform “what if…” type scenarios in attempts to improve the model and search for problem causes. Realistic applications in the accounting and health care areas are discussed.