Risk, cohabitation and marriage

This paper introduces imperfect information,learning,and risk aversion in a two sided matching model.The modelprovides a theoreticalframework for the com- monly occurring phenomenon of cohabitation followed by marriage,and is con- sistent with empirical findings on these institutions.The paper has three major results.First,individuals set higher standards for marriage than for cohabitation. When the true worth of a cohabiting partner is revealed,some cohabiting unions are converted into marriage while others are not.Second,individuals cohabit within classes.Third,the premium that compensates individuals for the higher risk involved in marriage over a cohabiting partnership is derived.This premium can be decomposed into two parts.The first part is a function of the individual ’s level of risk aversion,while the second part is a function of the di difference in risk between marriage and cohabitation.

As good as married : a model of long-term cohabitation, learning and marriage

This paper develops a two-sided search-matching model with imperfectly observed types and learning. Since agents do not observe one another’s type accurately, they first engage in a probationary partnership to learn one another’s true type. Using the metaphor ofpremarital cohabitation and marriage, we demonstrate that long-term cohabiting individuals eventually learn each other’s true type. We also demonstrate that singles ofeither sex are partitioned into classes and are matched in the same class in equilibrium. We show that sequential learning reduces signalling errors so that the Bayes estimator of the true type converges almost surely to true type. As noisy information is filtered over time, the mismatch risk disappears and the aggregate matching pattern based on true types is restored.

To Tie the Knot or Not

This paper introduces imperfect information, learning, and risk aversion in a two sided matching model. The model provides a theoretical framework for the commonly occurring phenomenon of cohabitation followed by marriage, and is consistent with empirical findings on these institutions. The paper has three major results. First, individuals set higher standards for marriage than for cohabitation. When the true worth of a cohabiting partner is revealed, some cohabiting unions are converted into marriage while others are not. Second, individuals cohabit within classes. Third, the premium that compensates individuals for the higher risk involved in marriage over a cohabiting partnership is derived. This premium can be decomposed into two parts. The first part is a function of the individual's level of risk aversion, while the second part is a function of the difference in risk between marriage and cohabitation.class partition, imperfect information, risk, stochastic dominance

Fence methods for mixed model selection

Many model search strategies involve trading off model fit with model complexity in a penalized goodness of fit measure. Asymptotic properties for these types of procedures in settings like linear regression and ARMA time series have been studied, but these do not naturally extend to nonstandard situations such as mixed effects models, where simple definition of the sample size is not meaningful. This paper introduces a new class of strategies, known as fence methods, for mixed model selection, which includes linear and generalized linear mixed models. The idea involves a procedure to isolate a subgroup of what are known as correct models (of which the optimal model is a member). This is accomplished by constructing a statistical fence, or barrier, to carefully eliminate incorrect models. Once the fence is constructed, the optimal model is selected from among those within the fence according to a criterion which can be made flexible. In addition, we propose two variations of the fence. The first is a stepwise procedure to handle situations of many predictors; the second is an adaptive approach for choosing a tuning constant. We give sufficient conditions for consistency of fence and its variations, a desirable property for a good model selection procedure. The methods are illustrated through simulation studies and real data analysis.Comment: Published in at http://dx.doi.org/10.1214/07-AOS517 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Risk, cohabitation and marriage

This paper introduces imperfect information,learning,and risk aversion in a two sided matching model.The modelprovides a theoreticalframework for the com- monly occurring phenomenon of cohabitation followed by marriage,and is con- sistent with empirical findings on these institutions.The paper has three major results.First,individuals set higher standards for marriage than for cohabitation. When the true worth of a cohabiting partner is revealed,some cohabiting unions are converted into marriage while others are not.Second,individuals cohabit within classes.Third,the premium that compensates individuals for the higher risk involved in marriage over a cohabiting partnership is derived.This premium can be decomposed into two parts.The first part is a function of the individual ’s level of risk aversion,while the second part is a function of the di difference in risk between marriage and cohabitation

Risk for Post-Spinal Surgery Complications Associated with Pre-Operative Blood Transfusions

Introduction: The frequency of spinal surgeries has increased dramatically in the United States over the past decade and, as with all surgeries, spinal procedures carry inherent risks for complications after the operation. Recently, it has been recognized that procedures in which intra-operative/post-operative blood transfusions are administered carry a higher risk of postoperative morbidity and increased length of hospital stay (Seisean et al.). Despite this, there is little literature, currently, analyzing post-operative complications associated with blood transfusions taking place 72 hours prior to spinal operations. The aim of this study was to investigate the prevalence of pre-operative blood transfusions in spinal surgeries and elucidate the associations that exist between those transfusions and post-operative complications. Materials & Methods: We retrospectively analyzed cases of spinal surgeries between 2005 and 2014 from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database with the exception of 2009 due to incomplete data. A total of 37,201 patients who had undergone spinal procedures were studied. Patients receiving pre-operative blood transfusions within 72 hours of surgery were documented. Demographic factors, including sex and age, were noted. Comorbidities included in this analysis include body mass index (BMI) and American Society of Anesthesiologists (ASA) score. Post-operative complications were stratified into major and minor categories. Chi-squared test, Fisher\u27s exact test, and ANOVA were used to perform univariate testing where appropriate, while multivariate analyses were performed to determine independent risk factors for complications. Results:With the exception of pneumonia (p=0.096), blood transfusions prior to spinal surgeries were associated with increased risk for all major and minor complication criteria analyzed, with major complications including myocardial infarction (MI), deep venous thrombosis (DVT), pulmonary embolism (PE), stroke, peripheral nerve injury, deep wound infection, organ cavity infection, sepsis, and death (p Discussion: Overall, patients receiving blood transfusions within 72 hours prior to undergoing spinal procedures had increased rates of several post-operative complications. Among these complications, the most notable include superficial and deep wound infections, MI, pneumonia, DVT, stroke, and even death. Armed with this knowledge, surgeons would better be able to predict, and therefore mitigate, such post-operative complications in these patients. Future research in this area, directed toward stratification of risk based on the patient’s need for pre-operative blood transfusion and procedure type, would provide further insight into preventing post-operative complications after spinal surgeries

Optimizing Network Performance of Computing Pipelines in Distributed Environments

Supporting high performance computing pipelines over wide-area networks is critical to enabling large-scale distributed scientific applications that require fast responses for interactive operations or smooth flows for data streaming. We construct analytical cost models for computing modules, network nodes, and communication links to estimate the computing times on nodes and the data transport times over connections. Based on these time estimates, we present the Efficient Linear Pipeline Configuration method based on dynamic programming that partitions the pipeline modules into groups and strategically maps them onto a set of selected computing nodes in a network to achieve minimum end-to-end delay or maximum frame rate. We implemented this method and evaluated its effectiveness with experiments on a large set of simulated application pipelines and computing networks. The experimental results show that the proposed method outperforms the Streamline and Greedy algorithms. These results, together with polynomial computational complexity, make our method a potential scalable solution for large practical deployments