Revisiting the Prediction of Financial Vulnerability

Whether or not a nonprofit organization is vulnerable to financial problems is a concern of all stakeholders of the organization. Recently, Greenlee and Trussel (2000) and Trussel and Greenlee (2001) expanded Tuckman and Chang's work (1991) to predict which organizations are financially vulnerable. This article extends the work of these authors by developing a model of financial vulnerability that includes four financial indicators, controls for the sector to which an organization belongs, and is based on a sample of over ninety‐four thousand organizations. The model is useful as a screening, monitoring, and attention‐getting device.     

Borrowing Information across Populations in Estimating Positive and Negative Predictive Values

A marker's capacity to predict risk of a disease depends on disease prevalence in the target population and its classification accuracy, i.e. its ability to discriminate diseased subjects from non-diseased subjects. The latter is often considered an intrinsic property of the marker; it is independent of disease prevalence and hence more likely to be similar across populations than risk prediction measures. In this paper, we are interested in evaluating the population-specific performance of a risk prediction marker in terms of positive predictive value (PPV) and negative predictive value (NPV) at given thresholds, when samples are available from the target population as well as from another population. A default strategy is to estimate PPV and NPV using samples from the target population only. However, when the marker's classification accuracy as characterized by a specific point on the receiver operating characteristics (ROC) curve is similar across populations, borrowing information across populations allows increased efficiency in estimating PPV and NPV. We develop estimators that optimally combine information across populations. We apply this methodology to a cross-sectional study where we evaluate PCA3 as a risk prediction marker for prostate cancer among subjects with or without previous negative biopsy.     

Testing for qualitative interaction of multiple sources of informative dropout in longitudinal data

Longitudinal studies suffer from patient dropout. The dropout process may be informative if there exists an association between dropout patterns and the rate of change in the response over time. Multiple patterns are plausible in that different causes of dropout might contribute to different patterns. These multiple patterns can be dichotomized into two groups: quantitative and qualitative interaction. Quantitative interaction indicates that each of the multiple sources is biasing the estimate of the rate of change in the same direction, although with differing magnitudes. Alternatively, qualitative interaction results in the multiple sources biasing the estimate of the rate of change in opposing directions. Qualitative interaction is of special concern, since it is less likely to be detected by conventional methods and can lead to highly misleading slope estimates. We explore a test for qualitative interaction based on simultaneous confidence intervals. The test accommodates the realistic situation where reasons for dropout are not fully understood, or even entirely unknown. It allows for an additional level of clustering among participating subjects. We apply these methods to a study exploring tumor growth rates in mice as well as a longitudinal study exploring rates of change in cognitive functioning for Alzheimer's patients.     

Longitudinal dynamic analyses of cognition in the health and retirement study panel

The purpose of this paper is to highlight some classic issues in the measurement of change and to show how contemporary solutions can be used to deal with some of these issues. Five classic issues will be raised here: (1) Separating individual changes from group differences; (2) options for incomplete longitudinal data over time, (3) options for nonlinear changes over time; (4) measurement invariance in studies of changes over time; and (5) new opportunities for modeling dynamic changes. For each issue we will describe the problem, and then review some contemporary solutions to these problems base on Structural Equation Models (SEM). We will fit these SEM to using existing panel data from the Health & Retirement Study (HRS) cognitive variables. This is not intended as an overly technical treatment, so only a few basic equations are presented, examples will be displayed graphically, and more complete references to the contemporary solutions will be given throughout.     

Vendor Selection with Bundling: A Comment*

In a recent article by Rosenthal, Zydiak, and Chaudhry (1995), a mixed integer linear programming model was introduced to solve the vendor selection problem for the case in which the vendor can sell items individually or as part of a bundle. Each vendor offered only one type of bundle, and the buyer could purchase at most one bundle per vendor. The model employed n(m+ 1) binary variables, where n is the number of vendors and m is the number of products they sell. The existing model can lead to a purchasing paradox: it may force the buyer to pay more to receive less. We suggest a reformulation of the same problem that (i) eliminates this paradox and reveals a more cost-effective purchasing strategy; (ii) uses only n integer variables and significantly reduces the computational workload; and (iii) permits the buyer to purchase more than one bundle per vendor.     

Marriage and Child Well-Being: Research and Policy Perspectives

Over the past decade, the linkages between marriage and child well-being have attracted the attention of researchers and policy makers alike. Children's living arrangements have become increasingly diverse and unstable, which raises important questions about how and why family structure and stability are related to child outcomes. This article reviews new research on this topic, emphasizing how it can inform policy debates about the role of marriage in reducing poverty and improving child outcomes. It also pays special attention to new scholarship on unmarried, primarily low-income families, the target of recent federal marriage initiatives, to appraise the potential contributions of family research to ongoing policy discussions.     

Sociology's misfortune: disciplines, interdisciplinarity and the impact of audit culture

This paper is about tendencies to the subversion of sociology as a discipline. It connects external factors of the wider socio-political environment of higher education in the UK, especially those associated with the audit culture and new systems of governance, with the internal organization of the discipline. While the environment is similar for all social science subjects, the paper argues that there are specific consequences for sociology because of characteristics peculiar to the discipline. The paper discusses these consequences in terms of the changing relationship between sociology and the growing interdisciplinary area of applied social studies as a form of 'mode 2 knowledge'. It argues that while sociology 'exports' concepts, methodologies and personnel it lacks the internal disciplinary integrity of other 'exporter' disciplines, such as economics, political science and anthropology. The consequence is an increasingly blurred distinction between sociology as a discipline and the interdisciplinary area of applied social studies with a potential loss of disciplinary identity. The paper concludes with a discussion of how this loss of identity is associated with a reduced ability to reproduce a critical sensibility within sociology and absorption to the constraints of audit culture with its preferred form of mode 2 knowledge.     

Labor‐Environmental Coalition Formation: Framing and the Right to Know1

This article examines the formation of a cross‐movement coalition between elements of the labor and environmental movements in New Jersey. We explain the successful formation and initial political campaign of the New Jersey Work Environment Council with an expansion of the theoretical perspective of frame analysis. We propose a model of a coalition collective action frame that offers several important insights into the active role coalition actors play in the construction of a common frame uniting union and environmental activists. Using qualitative data gathered from interviews, observations, and document analyses of two major campaigns, we argue that the coalition frame allowed new political opportunities to be created, leading to the establishment of the most sweeping right‐to‐know laws in the United States. We conclude the discussion of coalition framing by examining political constraints on the framing possibilities of coalitions, specifically by exploring how the discursive shift from the right to know to the right to act failed to expand the influence of the cross‐movement coalition as originally expected by its members.