Spatio-Temporal Modeling of Residential Sales Data

This article focuses on the location, time, and spatio-temporal components associated with suitably aggregated data to improve prediction of individual asset values. Such effects are introduced in the context of hierarchical models, which we find more natural than attempting to model covariance structure. Indeed, our cross-sectional database, a sample of 7,936 transactions for 49 subdivisions over a 10-year period in Baton Rouge, Louisiana, precludes covariance modeling. A wide range of models arises, each fitted using sampling-based methods because likelihood-based fitting may not be possible. Choosing among an array of nonnested models is carried out using a posterior predictive criterion. In addition, one year of data is held out for model validation. A thorough analysis of the data incorporating all of the aforementioned issues is presented.     

On the bias and mean square error of the least square estimator in a regression model with two inequality constraints and multivariate t error terms

We derive and numerically evaluate the bias and mean square error of the inequality constrained least squares estimator in a model with two inequality constraints and multivariate terror terms. Our results suggest that qualitatively, the estimator properties found for models with normal errors carry over to the case of multivariate terrors.     

Multiplicity: discussion points from the Statisticians in the Pharmaceutical Industry multiplicity expert group

In May 2012, the Committee of Health and Medicinal Products issued a concept paper on the need to review the points to consider document on multiplicity issues in clinical trials. In preparation for the release of the updated guidance document, Statisticians in the Pharmaceutical Industry held a one‐day expert group meeting in January 2013. Topics debated included multiplicity and the drug development process, the usefulness and limitations of newly developed strategies to deal with multiplicity, multiplicity issues arising from interim decisions and multiregional development, and the need for simultaneous confidence intervals (CIs) corresponding to multiple test procedures. A clear message from the meeting was that multiplicity adjustments need to be considered when the intention is to make a formal statement about efficacy or safety based on hypothesis tests. Statisticians have a key role when designing studies to assess what adjustment really means in the context of the research being conducted. More thought during the planning phase needs to be given to multiplicity adjustments for secondary endpoints given these are increasing in importance in differentiating products in the market place. No consensus was reached on the role of simultaneous CIs in the context of superiority trials. It was argued that unadjusted intervals should be employed as the primary purpose of the intervals is estimation, while the purpose of hypothesis testing is to formally establish an effect. The opposing view was that CIs should correspond to the test decision whenever possible. Copyright © 2013 John Wiley & Sons, Ltd.     

Reputation in Rupture: Broken Alliances and Relational Politics in the Roosevelt-Taft Split

Under what circumstances do close allies sacrifice their unity? By what process do bonds break? Although it might be argued that political ruptures are determined by incommensurable ideas (policies, philosophies) or by contentious personalities (temperament, character), we argue that neither explanation is sociologically sufficient. Extending the theories of interpersonal ruptures of Diane Vaughan and Robert Emerson to political domains, we take a relational approach to politics by emphasizing the centrality of the availability of reputational information, networks of supporters, and public displays of antagonism in response to affronts within systems of institutional power. Our approach to public ruptures draws on a detailed case study: the broken alliance between presidents Theodore Roosevelt and William Howard Taft, a dramatic instance of changing master-protégé relationship. The transition from close interpersonal alliance to public distaste typically involves four stages that expand a relational breach to an irreparable rupture: (1) personal grievance, (2) substantive disagreement, (3) public awareness, and (4) network activity. While every detailed case has limits, we note comparable instances and contend that this model applies broadly to broken partnerships in politics or other public domains.     

How does family health care use respond to economic shocks? realized and anticipated effects

Review of Economics of the Household - Using two-year panel data from the Medical Expenditure Panel Survey (MEPS) for 2004 to 2012, we examine how the intra-family allocation of health care...     

NGOs’ transnational advocacy networks: from ‘legitimacy’ to ‘political responsibility’?

NGOs that operate as part of transnational advocacy networks face a number of ‘legitimacy challenges’ concerning their rights to participate in the shaping of global governance. Outlining the legitimacy claims that development NGOs make, the article argues that ‘legitimacy’ is a socially constructed quality that may be ascribed to an NGO by actors and stakeholders with different viewpoints. NGOs operating transnationally link disparate communities and conceptions of legitimacy, and undermine the discourse and practice of sovereignty. Therefore such NGOs will find it difficult to be universally regarded as legitimate, especially by states that hold a sovereignty‐based conception of legitimacy. However, relationships are the building blocks of networks, and efforts to improve them should not be abandoned simply because ‘legitimacy’ is too closely connected with sovereignty. In particular, NGOs ought to improve their relationships with the poor and marginalized communities whose interests they claim to promote. To this end, the concept of ‘political responsibility’ is suggested as a pragmatic approach to understanding power relations as they arise in transnational advocacy networks and campaigns.     

Using Conditioned Reinforcers to Improve Behavior-Change Skills: Clicker Training for Practitioners

We evaluated the use of a clicker sound as a conditioned reinforcer to teach behavior interventionists appropriate clinical skills during in-situ training. A multiple-baseline-across-behaviors design indicated that the intervention was effective in increasing all target behaviors for all participants. For two of the participants, we conducted maintenance probes one to five weeks after the final training session and performance continued to occur at a high level. Although the participants ranked the contingent clicker presentation as less disruptive and more fair than typical feedback methods, they ranked it as slightly less helpful, less worthwhile, and less pleasant than typical feedback methods. These findings suggest that clicker training can play a valuable role in training mental health professionals.     

Tricks and Reveries

Qualitative Sociology -     

Analyzing space-time sensor network data under suppression and failure in transmission

In this paper we present a fully model-based analysis of the effects of suppression and failure in data transmission with sensor networks. Sensor networks are becoming an increasingly common data collection mechanism in a variety of fields. Sensors can be created to collect data at very high temporal resolution. However, during periods when the process is following a stable path, transmission of such high resolution data would carry little additional information with regard to the process model, i.e., all of the data that is collected need not be transmitted. In particular, when there is cost to transmission, we find ourselves moving to consideration of suppression in transmission. Additionally, for many sensor networks, in practice, we will experience failures in transmission—messages sent by a sensor but not received at the gateway, messages sent but arriving corrupted. Evidently, both suppression and failure lead to information loss which will be reflected in inference associated with our process model. Our effort here is to assess the impact of such information loss under varying extents of suppression and varying incidence of failure. We consider two illustrative process models, presenting fully model-based analyses of suppression and failure using hierarchical models. Such models naturally facilitate borrowing strength across nodes, leveraging all available data to learn about local process behavior.