Loss functions for estimation of extrema with an application to disease mapping

It is often of interest to find the maximum or near maxima among a set of vector‐valued parameters in a statistical model; in the case of disease mapping, for example, these correspond to relative‐risk “hotspots” where public‐health intervention may be needed. The general problem is one of estimating nonlinear functions of the ensemble of relative risks, but biased estimates result if posterior means are simply substituted into these nonlinear functions. The authors obtain better estimates of extrema from a new, weighted ranks squared error loss function. The derivation of these Bayes estimators assumes a hidden‐Markov random‐field model for relative risks, and their behaviour is illustrated with real and simulated data.     

Consistent maximum likelihood estimation of a unimodal density using shape restrictions

It is well known that the unimodal maximum likelihood estimator of a density is consistent everywhere but at the mode. The authors review various ways to solve this problem and propose a new estimator that is concave over an interval containing the mode; this interval may be chosen by the user or through an algorithm. The authors show how to implement their solution and compare it to other approaches through simulations. They show that the new estimator is consistent everywhere and determine its rate of convergence in the Hellinger metric.     

An empirical examination of cost-adjusting in outpatient clinics

This paper presents an empirical methodology for examining cost-adjusting in relation to multiple-output health care providers. The methodology is subsequently implemented using a sample of California outpatient clinics. The empirical evidence is that these clinics do cost-adjust; that is, the clinics respond to low Medicare reimbursement by using lower quality to control the marginal costs of those patient groups not insured under a government-sponsored plan. In addition, clinics do not cost-adjust with respect to Medi-Cal patients, implying that various government reimbursement systems have different effects on a provider’s cost-adjusting behavior.     

English Language Proficiency of Immigrants and Refugees in the Twin Cities Metropolitan Area

Studies of the determinants of English language ability have generally focused on the largest immigrant groups in the United States. Much less is known about smaller, but significant regional concentrations of immigrants and refugees. This article presents data on four very distinct and understudied groups: Russians, Somalis, Hmong, and Mexicans in the Midwest. We found large differences in English language proficiency across the different national origin groups, even after controlling for background variables. These differences were not attributable to refugee status or to linguistic distance from English. Being Somali, migrating to the United States at a young age and having a college diploma were the best predictors of both spoken and written proficiency. The returns to higher education were particularly noteworthy — respondents with college diplomas were more than 29 times more likely than non‐high school graduates to speak English well, and more than 20 times as likely to read well. Women appear to have benefited more than men from completing college in terms of spoken English proficiency since the male‐female gap narrows among the highly educated. Length of time in the United States was a good predictor of whether an individual speaks English at home, regardless of age of entry to the country.     

An Empirical Examination of Quality Certification in a "Lemons Market"

This article examines the effect third-party certification has on a market characterized by adverse selection. Using an original data set from the market for young thoroughbreds, we show that certification alleviates problems of adverse selection by examining the effect certification has on breeder decisions to retain or sell horses and the effect these decisions have on observed prices. Data on the racetrack performance of the horses confirm the results.     

A simple estimator for a shared frailty regression model

Summary. We propose a simple estimation procedure for a proportional hazards frailty regression model for clustered survival data in which the dependence is generated by a positive stable distribution. Inferences for the frailty parameter can be obtained by using output from Cox regression analyses. The computational burden is substantially less than that of the other approaches to estimation. The large sample behaviour of the estimator is studied and simulations show that the approximations are appropriate for use with realistic sample sizes. The methods are motivated by studies of familial associations in the natural history of diseases. Their practical utility is illustrated with sib pair data from Beaver Dam, Wisconsin.