A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.     

Implied Preference for Seismic Design Level and Earthquake Insurance

Seismic risk can be reduced by implementing newly developed seismic provisions in design codes. Furthermore, financial protection or enhanced utility and happiness for stakeholders could be gained through the purchase of earthquake insurance. If this is not so, there would be no market for such insurance. However, perceived benefit associated with insurance is not universally shared by stakeholders partly due to their diverse risk attitudes. This study investigates the implied seismic design preference with insurance options for decisionmakers of bounded rationality whose preferences could be adequately represented by the cumulative prospect theory (CPT). The investigation is focused on assessing the sensitivity of the implied seismic design preference with insurance options to model parameters of the CPT and to fair and unfair insurance arrangements. Numerical results suggest that human cognitive limitation and risk perception can affect the implied seismic design preference by the CPT significantly. The mandatory purchase of fair insurance will lead the implied seismic design preference to the optimum design level that is dictated by the minimum expected lifecycle cost rule. Unfair insurance decreases the expected gain as well as its associated variability, which is preferred by risk-averse decisionmakers. The obtained results of the implied preference for the combination of the seismic design level and insurance option suggest that property owners, financial institutions, and municipalities can take advantage of affordable insurance to establish successful seismic risk management strategies.     

说一切有部的弥勒观

学界一般认为古代龟兹是小乘说一切有部文化中心,克孜尔中心柱窟图像构成是小乘僧人一佛一菩萨(弥勒)崇拜的反映.本文探讨了说一切有部对弥勒菩萨的态度.从与说一切有部相关的典籍中检索出有关弥勒的文献并进行分析,最后发现这个部派其实反对弥勒崇拜,这使我们重新审视传统理论的两个方面--克孜尔石窟的教派属性,以及弥勒菩萨的图像志.     

Robust testing with generalized partial linear models for longitudinal data

By approximating the nonparametric component using a regression spline in generalized partial linear models (GPLM), robust generalized estimating equations (GEE), involving bounded score function and leverage-based weighting function, can be used to estimate the regression parameters in GPLM robustly for longitudinal data or clustered data. In this paper, score test statistics are proposed for testing the regression parameters with robustness, and their asymptotic distributions under the null hypothesis and a class of local alternative hypotheses are studied. The proposed score tests reply on the estimation of a smaller model without the testing parameters involved, and perform well in the simulation studies and real data analysis conducted in this paper.     

Interpreting DNA Mixtures with Related Contributors in Subdivided Populations

Abstract.  In this paper, we study the statistical interpretation of forensic DNA mixtures with related contributors in subdivided populations. Compact general formulae for match probabilities are obtained for two situations: a relative of one tested person is an unknown contributor of a DNA mixture; and two related unknowns are contributors. The effect of kinship and population structure is illustrated using a real case example.     

An introduction to econometric applications of empirical process theory for dependent random variables

This paper discusses some uses in econometrics of empirical process theory for dependent rendom variables. Examples considered include non-standard parametric hypotheses tests and semiparametric estimation. The application of bracketing functional limit results is discussed in some detail     

Screening for patients with alcohol problems: severity of patients identified by the CAGE.

Primary care physicians are well situated to identify patients with substance abuse problems and motivate them to seek appropriate assistance, but active programs are the exception. A study in a community setting was undertaken to assess the CAGE (the first letters of key words in a series of four questions about drinking: cut down; annoyed; guilty; and eye-opener), instrument in the routine screening for alcohol problems in both new and established patients. The screening process identified subjects for a pilot evaluation of a motivational interview designed to encourage problem-solving behavior. This article focuses on the screening results and the use of the CAGE instrument. During June and July of 1990, 687 patients of two primary care physicians belonging to a large group practice were asked to complete a health questionnaire that included the CAGE. Those who responded affirmatively to at least two of the four CAGE questions were requested to participate in follow-up assessment of problems associated with alcohol and health. The type and severity of alcohol problems experienced by patients who scored positive on the CAGE are described. Prevalence of a positive score on the CAGE was 8.6 percent with males, smokers, and blue collar and unemployed persons being more likely to score positive. The positive predictive value was .68. Primarily, persons with moderate alcohol problems were identified. Results show that the CAGE instrument is a useful screening device for identifying those with mild to moderate substance abuse problems, increasing the opportunity for intervention prior to serious medical complications. The instrument is easily administered, and has demonstrated relatively high levels of sensitivity and specificity. When combined with assessment and motivational interviews, the CAGE shows promise in the secondary prevention of substance abuse and related health problems.