Network Model Selection for Task-Focused Attributed Network Inference

Networks are models representing relationships between entities. Often these relationships are explicitly given, or we must learn a representation which generalizes and predicts observed behavior in underlying individual data (e.g. attributes or labels). Whether given or inferred, choosing the best representation affects subsequent tasks and questions on the network. This work focuses on model selection to evaluate network representations from data, focusing on fundamental predictive tasks on networks. We present a modular methodology using general, interpretable network models, task neighborhood functions found across domains, and several criteria for robust model selection. We demonstrate our methodology on three online user activity datasets and show that network model selection for the appropriate network task vs. an alternate task increases performance by an order of magnitude in our experiments

The Preadult Origins of Post-Materialism: A Longitudinal Sibling Study

Using a research design that traces siblings preferences for postmaterialistic values in Germany over two decades, this paper provides new evidence on the origins of value preferences. Focusing on Inglehart's thesis of value change, we test the combined socialization and scarcity hypothesis against the social learning hypothesis, a prominent rival account of preadult value preference formation. Sibling estimates show that the shared preadult environment does indeed exert lasting effects on the permanent component of preferences for post-materialistic policies. In addition to weak effect of the shared experience of socioeconomic scarcity, we find that the intergenerational transmission of postmaterialism -which is disregarded by Inglehart's original thesis- plays a significant role in value preference acquisition. We discuss the implications of our individual-level findings for forecasts of aggregate-level trends in value change.

A methodology to measure hospital quality using physicians' choices over training vacancies

In this paper, we propose an alternative methodology to rank hospitals based on the choices of Medical Schools graduates over training vacancies. We argue that our measure of relative hospital quality has the following desirable properties: a) robustness to manipulation from the hospital's administrators; b) comprehensiveness in the scope of the services analyzed; c) inexpensive in terms of data requirements, and d) not subject to selection biases. Accurate measures of health provider quality are needed in order to establish incentive mechanisms, to assess the need for quality improvement, or simply to increase market transparency and competition. Public report cards in certain US states and the NHS ranking system in the UK are two attempts at constructing quality rankings of health care providers. Although the need for such rankings is widely recognized, the criticisms at these attempts reveal the difficulties involved in this task. Most criticisms alert to the inadequate risk-adjustment and the potential for perverse consequences such as patient selection. The recent literature, using sophisticated econometric models is capable of controlling for case-mix, hospital and patient selection, and measurement error. The detailed data needed for these evaluations is, however, often unavailable to researchers. In those countries, such as Spain, where there is neither public hospital rankings nor public data on hospital output measures such as mortality rates our methodology is a valid alternative. We develop this methodology for the Spanish case. In a follow-up paper we will present results using Spanish data. In Spain graduates choose hospital training vacancies in a sequential manner that depends on their average grade. Our framework relies on three assumptions. First, high quality hospitals provide high quality training. Second, graduates are well informed decision makers who are well qualified to assess hospital quality. Third, they prefer to choose a high quality vacancy rather than a low quality one ceteris paribus. If these assumptions hold, then the first physicians to choose are likely to grab the best vacancies while the ones who choose last are stuck with the worst available. Thus, it is possible to infer from physicans' choices quality differentials amongst hospitals. We model the physician's decision as a nested-logit a la McFadden. Unlike in standard applications of McFadden's model, in our application the choice set is not constant across physicians but it shrinks along the sequential hospital choice proces

Recursive Thick Modeling and the Choice of Monetary Policy in Mexico

By following the spirit in Favero and Milani (2005), we use recursive thick modeling to take into account model uncertainty for the choice of optimal monetary policy. We consider an open economy model and generate multiple models for only the aggregate demand and aggregate supply. Models are constructed by matching the rankings of aggregate demand and aggregate supply and adding other specifications for the rest of the variables. The main results show that recursive thick modeling with equal and different weights approximates the recent historical behavior of nominal interest rates in Mexico better than recursive thin modelingmodel uncertainty, optimal control, out-of-bag, thin modeling and thick modeling

Shortest path or anchor-based route choice: a large-scale empirical analysis of minicab routing in London

Understanding and modelling route choice behaviour is central to predicting the formation and propagation of urban road congestion. Yet within conventional literature disagreements persist around the nature of route choice behaviour, and how it should be modelled. In this paper, both the shortest path and anchor-based perspectives on route choice behaviour are explored through an empirical analysis of nearly 700,000 minicab routes across London, United Kingdom. In the first set of analyses, the degree of similarity between observed routes and possible shortest paths is established. Shortest paths demonstrate poor performance in predicting both observed route choice and characteristics. The second stage of analysis explores the influence of specific urban features, named anchors, in route choice. These analyses show that certain features attract more route choices than would be expected were individuals choosing route based on cost minimisation alone. Instead, the results indicate that major urban features form the basis of route choice planning – being selected disproportionately more often, and causing asymmetry in route choice volumes by direction of travel. At a finer scale, decisions made at minor road features are furthermore demonstrated to influence routing patterns. The results indicate a need to revisit the basis of how routes are modelled, shifting from the shortest path perspective to a mechanism structured around urban features. In concluding, the main trends are synthesised within an initial framework for route choice modelling, and presents potential extensions of this research

Factors determining patients’ intentions to use point-of-care testing medical devices for self-monitoring: The case of international normalised ratio self-testing

This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited. - Copyright @ 2012 Dove Medical Press LtdThis article has been made available through the Brunel Open Access Publishing Fund.Purpose: To identify factors that determine patients' intentions to use point-of-care medical devices, ie, portable coagulometer devices for self-testing of the international normalized ratio (INR) required for ongoing monitoring of blood-coagulation intensity among patients on long-term oral anticoagulation therapy with vitamin K antagonists, eg, warfarin. Methods: A cross-sectional study that applied the technology-acceptance model through a self-completed questionnaire, which was administered to a convenience sample of 125 outpatients attending outpatient anticoagulation services at a district general hospital in London, UK. Data were analyzed using descriptive statistics, factor analyses, and structural equation modeling. Results: The participants were mainly male (64%) and aged ≥ 71 years (60%). All these patients were attending the hospital outpatient anticoagulation clinic for INR testing; only two patients were currently using INR self-testing, 84% of patients had no knowledge about INR self-testing using a portable coagulometer device, and 96% of patients were never offered the option of the INR self-testing. A significant structural equation model explaining 79% of the variance in patients’ intentions to use INR self-testing was observed. The significant predictors that directly affected patients' intention to use INR self-testing were the perception of technology (β = 0.92, P < 0.001), trust in doctor (β = −0.24, P = 0.028), and affordability (β = 0.15, P = 0.016). In addition, the perception of technology was significantly affected by trust in doctor (β = 0.43, P = 0.002), age (β = −0.32, P < 0.001), and affordability (β = 0.23, P = 0.013); thereby, the intention to use INR self-testing was indirectly affected by trust in doctor (β = 0.40), age (β = −0.29), and affordability (β = 0.21) via the perception of technology. Conclusion: Patients’ intentions to use portable coagulometers for INR self-testing are affected by patients' perceptions about the INR testing device, the cost of device, trust in doctors/clinicians, and the age of the patient, which need to be considered prior to any intervention involving INR self-testing by patients. Manufacturers should focus on increasing the affordability of INR testing devices for patients’ self-testing and on the potential role of medical practitioners in supporting use of these medical devices as patients move from hospital to home testing.This study is funded by the Multidisciplinary Assessment of Technology Centre for Healthcare (MATCH) program (EPSRC grant EP/GO12393/1)

Grants, Contracts and the Division of Labor in Academic Research

This paper aims to shed light on the division of labor among types of research sponsors and among universities. It interprets data on grants and contracts as conveying information on the sponsorsÂ’ objectives and on the nature of the sponsored institutions. Building on this idea, the paper investigates some notions that appear to be fairly common: That more prestigious universities tend to rely more on grant funding relative to contract funding; that less prestigious research universities tend to rely more heavily on contracts; that grant (contract) funding tends to be associated with basic (applied) research; and that types of sponsors differ in their use of grants versus contracts, depending on their institutional commitment to knowledge as a public good.