A semiparametric shock model for a pair of event-related dependent censored failure times

In this paper, we propose a semiparametric shock model for two dependent failure times where the risk indicator of one failure time plays the part of a time-varying covariate for the other one. According to Hougaard [2000. Analysis of Multivariate Survival Data. Springer, New York], the dependence between the two failure times is therefore of event-related type.     

Survey response and survey characteristics: microlevel evidence from the European Community Household Panel

Summary.  The paper presents microlevel evidence on the role of the sociodemographic characteristics of a population and the characteristics of the data collection process as predictors of survey response. Our evidence is based on the public use files of the European Community Household Panel, a longitudinal household survey covering the countries of the European Union, whose attractive feature is the high level of comparability across countries and over time. We model the response process as the outcome of two sequential events: contact between the interviewer and an eligible interviewee, and co-operation by the interviewee. Our model allows for dependence between the ease of contact and the propensity to co-operate, taking into account the censoring problem caused by the fact that we observe whether a person is a respondent only if she has been contacted.     

Variation within households in consent to link survey data to administrative records: evidence from the UK Millennium Cohort Study

This study expands our knowledge of consent in linking survey and administrative data by studying respondents’ behaviour when consenting to link their own records and when consenting to link those of their children. It develops and tests a number of hypothesised mechanisms of consent, some of which were not explored in the past. The hypotheses cover: parental pride, privacy concerns, loyalty to the survey, pre-existing relations with the agency holding the data, and interviewer effects. The study uses data from the longitudinal Millennium Cohort Study to analyse the correlates of consent in multiple domains (i.e. linkage of education, health and economic records). The findings show that respondent’s behaviour vary depending on the consent domain and on the person within the household for whom consent is sought. In particular, the cohort member’s cognitive skills and the main respondent’s privacy concerns have differential effects on consent. On the other hand, loyalty to the survey proxied by the longitudinal response history has a significant and strong impact on consent irrespective of the outcome. The findings also show that interviewers account for a large proportion of variations in consent even after controlling for the characteristics of the interviewer’s assignment area. In total, it is possible to conclude that the significant impact of some of the correlates will lead to sample bias which needs to be accounted for when working with linked survey and administrative data.     

A Monte Carlo comparison of alternative methods of maximum likelihood ranking in racing sports

Applications of maximum likelihood techniques to rank competitors in sports are commonly based on the assumption that each competitor's performance is a function of a deterministic component that represents inherent ability and a stochastic component that the competitor has limited control over. Perhaps based on an appeal to the central limit theorem, the stochastic component of performance has often been assumed to be a normal random variable. However, in the context of a racing sport, this assumption is problematic because the resulting model is the computationally difficult rank-ordered probit. Although a rank-ordered logit is a viable alternative, a Thurstonian paired-comparison model could also be applied. The purpose of this analysis was to compare the performance of the rank-ordered logit and Thurstonian paired-comparison models given the objective of ranking competitors based on ability. Monte Carlo simulations were used to generate race results based on a known ranking of competitors, assign rankings from the results of the two models, and judge performance based on Spearman's rank correlation coefficient. Results suggest that in many applications, a Thurstonian model can outperform a rank-ordered logit if each competitor's performance is normally distributed.     

我国居民医疗需求影响因素的实证分析——有序probit模型的半参数估计

本文以个人潜在医疗需求为潜变量,以表示患病情况的有序离散变量为被解释变量,建立了有序probit回归模型,日的在于考察年龄、收入、性别、教育等主要个人人口特征和经济社会地位变量对医疗需求的影响.本文实证分析采用的是中国健康与营养调查2004年的微观调奁数据,采用半参数方法对模型进行了估计.估计结果显示:年龄、性别、婚姻状态、居住在农村、收入水平、教育水平对个人的医疗需求有不同程度的影响.实证分析结果对于预测我国医疗费用的发展趋势和缓和医疗服务中的不平等问题都有参考价值.     

Adaptive designs for selecting drug combinations based on efficacy–toxicity response

We propose a new adaptive procedure for dose-finding in clinical trials with combination of two drugs when both efficacy and toxicity responses are available. We model the distribution of this bivariate binary endpoint using the bivariate probit model. The analytic formulae for the Fisher information matrix are obtained, that form the basis for derivation of the locally optimal, minimax, Bayesian, and adaptive designs in the framework of optimal design theory.     

Bivariate prior distributions via branching exchangeable sequences

This paper provides a novel approach to constructing bivariate prior distributions. The idea is based on the notion of partial exchangeability. In particular, in a simple extension of the exchangeable sequence, we create two dependent exchangeable sequences via a branching mechanism. This implies the existence of a bivariate prior distribution.     

Quantal resp0nse assays by inverse regression

A general inverse regression procedure for estimating dose-response curves in quanta1 response assays is presented. Asymptotic distributional properties are developed. The special case is given, where after suitable transformation, the -dose response curve is linear. The inverse method has a decided advantage over the more classical methods in this case, both inflexibility and in ease of application. The procedure will be shown to be fully efficient, in the asymptotic context*     

Large sample tests for testing symmetry and independence in some bivariate exponential models

Bivariate Exponential Distribution (BVED) were introduced by Freund (1961), Marshall and Olkin (1967) and Block and Basu (1974) as models for the distributions of (X,Y) the failure times of dependent components (C₁,C₂). We study the structure of these models and observe that Freund model leads to a regular exponential family with a four dimensional orthogonal parameter. Marshall-Olkin model involving three parameters leads to a conditional or piece wise exponential family and Block-Basu model which also depends on three parameters is a sub-model of the Freund model and is a curved exponential family. We obtain a large sample tests for symmetry as well as independence of (X,Y) in each of these models by using the Generalized Likelihood Ratio Tests (GLRT) or tests basesd on MLE of the parameters and root n consistent estimators of their variance-covariance matrices.     

Conditional Extremes in Asymmetric Financial Markets

ABSTRACT

The global financial crisis of 2007–2009 revealed the great extent to which systemic risk can jeopardize the stability of the entire financial system. An effective methodology to quantify systemic risk is at the heart of the process of identifying the so-called systemically important financial institutions for regulatory purposes as well as to investigate key drivers of systemic contagion. The article proposes a method for dynamic forecasting of CoVaR, a popular measure of systemic risk. As a first step, we develop a semi-parametric framework using asymptotic results in the spirit of extreme value theory (EVT) to model the conditional probability distribution of a bivariate random vector given that one of the components takes on a large value, taking into account important features of financial data such as asymmetry and heavy tails. In the second step, we embed the proposed EVT method into a dynamic framework via a bivariate GARCH process. An empirical analysis is conducted to demonstrate and compare the performance of the proposed methodology relative to a very flexible fully parametric alternative.