Random effects and shrinkage estimation in capture-recapture models

We discuss the analysis of random effects in capture-recapture models, and outline Bayesian and frequentists approaches to their analysis. Under a normal model, random effects estimators derived from Bayesian or frequentist considerations have a common form as shrinkage estimators. We discuss some of the difficulties of analysing random effects using traditional methods, and argue that a Bayesian formulation provides a rigorous framework for dealing with these difficulties. In capture-recapture models, random effects may provide a parsimonious compromise between constant and completely time-dependent models for the parameters (e.g. survival probability). We consider application of random effects to band-recovery models, although the principles apply to more general situations, such as Cormack-Jolly-Seber models. We illustrate these ideas using a commonly analysed band recovery data set.     

Near‐Misses and Future Disaster Preparedness

Disasters garner attention when they occur, and organizations commonly extract valuable lessons from visible failures, adopting new behaviors in response. For example, the United States saw numerous security policy changes following the September 11 terrorist attacks and emergency management and shelter policy changes following Hurricane Katrina. But what about those events that occur that fall short of disaster? Research that examines prior hazard experience shows that this experience can be a mixed blessing. Prior experience can stimulate protective measures, but sometimes prior experience can deceive people into feeling an unwarranted sense of safety. This research focuses on how people interpret near‐miss experiences. We demonstrate that when near‐misses are interpreted as disasters that did not occur and thus provide the perception that the system is resilient to the hazard, people illegitimately underestimate the danger of subsequent hazardous situations and make riskier decisions. On the other hand, if near‐misses can be recognized and interpreted as disasters that almost happened and thus provide the perception that the system is vulnerable to the hazard, this will counter the basic “near‐miss” effect and encourage mitigation. In this article, we use these distinctions between resilient and vulnerable near‐misses to examine how people come to define an event as either a resilient or vulnerable near‐miss, as well as how this interpretation influences their perceptions of risk and their future preparedness behavior. Our contribution is in highlighting the critical role that people's interpretation of the prior experience has on their subsequent behavior and in measuring what shapes this interpretation.     

Integrating strategic issues into strategic management

The notion of a ‘strategic issues’ is rather pervasive in the field of planning in both conceptual [5, 19] and practical contexts. For instance, sometime ago the Wall Street Journal [41] reported that at least 50 large firms have created positions of ‘issues management director’; a dramatic increase in the number of such positions. ‘True’ strategic issues have a readily apparent importance to any organization; yet the process of identifying such issues and of integrating them into strategic planning and management is not well developed. Most treatments of strategic issues deal only with specific segments of the overall process through which relevant issues may be initially identified and finally translated into appropriate strategy [e.g. 5, 17]. This paper demonstrates that it is practical to develop a comprehensive process of ‘strategic issue management’ (SIM) that will facilitate the systematic identification, assessment and analysis of such issues. Such a process can ensure that issue-related factors are fully integrated into the formulation and implementation of strategy and plans. As such, SIM is a process whereby strategic issues may become an integral element of strategic management.     

Positive and negative affect: A maximum-likelihood approach

Using the LISREL maximum-likelihood program, the relation between Bradburn's positive affect and negative affect scales is examined for three age groups of adults. It is found that (a) unequal item loadings fit significantly better than equal item loadings; (b) the best-fitting loadings for the elderly are significantly different from those of the non-elderly; (c) the positive and negative affect scales are substantially correlated and (d) correlations with related variables are stronger when positive and negative affect scales are formed by maximum-likelihood loadings rather than by unit loadings. Given the widespread use of Bradburn's scales, implications of these results for subjective well-being are discussed.     

THE FAMILY FIRO MODEL: A MODEST PROPOSAL FOR ORGANIZING FAMILY TREATMENT

This paper presents a model for organizing family issues and family treatment. Schutz's FIRO model is offered as a framework for organizing family issues into inclusion, control and affection categories. Following Schutz's theory of group development, we propose that inclusion, control and affection constitute a logical hierarchy of core issues to be dealt with in treating multiproblem families-inclusion first, then control, and then affection (intimacy). Furthermore, we propose that the FIRO model can be used to organize theories of family therapy. We attempt to demonstrate that different family therapies are best suited for one of the three core issues of family interaction. We advocate an "intelligent eclecticism" based on the premise that when an issue is appropriately matched with a therapy, therapeutic effectiveness should be enhanced. We also discuss implications of our Family FIRO model for clinical practice.     

Latent classes and group membership

A technique for analyzing group membership data, such as interlocking directorates, based on the assumption of latent classes of individuals, is described and illustrated with two data sets. The technique partitions individuals and/or groups into homogeneous sets and can be used to create measures of structural centrality for groups and for individuals.     

Jackknifing in Categorical Data Analysis

Estimation of nonlinear functions of a multinomial parameter vector is necessary in many categorical data problems. The first and second order jackknife are explored for the purpose of reduction of bias. The second order jackknife of a function g(.) of a multinomial parameter is shown to be asymptotically normal if all second order partials ?²g( p )?dp_i?p_j obey a Hölder condition with exponent α>1/2. Numerical results for the estimation of the log odds ratio in a 2times2 table demonstrate the efficiency of the jackknife method for reduction of mean-square-error and the construction of approximate confidence intervals.     

The last mile of the way: understanding caregiving in African American families at the end-of-life

This research is based on in-depth ethnographic interviews and focus groups with 88 African American family caregivers from various regions of the United States during a stressful time in their family development--caregiving at the end-of-life--and the grieving during the aftermath. The study employed a stratified purposeful sampling strategy. Subjects were African Americans from the Northern, Southern, and Midwestern United States. Formal care is complicated by the distrust that many African Americans hold toward the health care system, which has resulted from years of exclusion, racism and discrimination. The findings highlight the importance of hearing from African American families to gain an understanding of what services, including family therapy and other psychotherapy, they will need during this process.