Use of Cohort Information in the Design and Analysis of Case-Control Studies

Abstract.  Four case studies are presented to illustrate how information available on cohort members can be used to inform the control selection in epidemiologic case-control studies. The basic framework is the nested case-control paradigm and accompanying analysis methods. Emphasis is on development of intuition for choosing study design candidates, the form of the estimators, and extensions of the basic theory to solve design and analysis problems.     

Effect of frailty on marginal regression estimates in survival analysis

Unexplained heterogeneity in univariate survival data and association in multivariate survival can both be modelled by the inclusion of frailty effects. This paper investigates the consequences of ignoring frailty in analysis, fitting misspecified Cox proportional hazards models to the marginal distributions. Regression coefficients are biased towards 0 by an amount which depends in magnitude on the variability of the frailty terms and the form of frailty distribution. The bias is reduced when censoring is present. Fitted marginal survival curves can also differ substantially from the true marginals.     

解冻温度对牛颗粒冷冻精液品质影响的初步研究

取同一种公牛一次采精冷冻的颗粒精液进行不同温度的解冻试验，观察解冻温度对解冻精液品质的影响。实验结果证明，解冻温度对解冻后精子活力、畸形率和顶体完整率有显著性影响（P＜0．01），与精子活力和顶体完整率呈正相关（r值分别为0．83和0．94），与精子畸形率呈负相关（r值为－0．97）。解冻温度对解冻后精子存活时间无显著性影响（p＞0.05）。在本次实验中，解冻温度以65℃和75℃为最优，显著优于目前普遍采用的38—40℃。     

日本武士的生存土壤

武士的产生，有其深刻的经济、政治和军事动因。庄园制的兴起奠定了武士产生的经济基础，武力争夺土地的斗争造就了武士以武为本的生存土壤；各派政治势力争权夺势的政治斗争，为武士的产生和发展推波助澜，使武士的活动舞台从经济领域扩展到政治领域；中央集权常备兵制瓦解和军事力量虚弱化，军队无力履行国家政权支柱的职能，武士乘势蚕食其武力空间。武士适应武力争夺经济资源的需要而产生，以争夺财富和权力的武装斗争为生存土壤，以杀戮技能为生存资本，在征战杀伐中发展壮大。     

On a Bivariate Distribution with Exponential Marginals

A new bivariate distribution with exponential marginals has been introduced by Singpurwalla & Youngren (1993). This distribution is absolutely continuous and has a single parameter. It was originally motivated as the failure model for a two-component system experiencing damage described by a shot–noise process. The purpose of this paper is two-fold. The first is to articulate on several aspects of this distribution, in particular, its genesis, the nature of its dependence, its correlation structure, and its generalized version as a two-parameter bivariate distribution with exponential marginals. The second purpose of this paper is more general. Prompted by the need to explain certain features of the bivariate distribution, it is found useful to introduce a new notion in reliability and survival analysis. This notion is called the "hazard potential", of an item susceptible to failure. The hazard potential is viewed as a kind of hidden parameter of failure models that delineates a cause and effect relationship in reliability.     

Bayesian Semiparametric Cure Rate Model with an Unknown Threshold

Abstract.  We propose a Bayesian semiparametric model for survival data with a cure fraction. We explicitly consider a finite cure time in the model, which allows us to separate the cured and the uncured populations. We take a mixture prior of a Markov gamma process and a point mass at zero to model the baseline hazard rate function of the entire population. We focus on estimating the cure threshold after which subjects are considered cured. We can incorporate covariates through a structure similar to the proportional hazards model and allow the cure threshold also to depend on the covariates. For illustration, we undertake simulation studies and a full Bayesian analysis of a bone marrow transplant data set.     

Technological and Output Complementarities, and Inter-Firm Cooperation in Information Technology Ventures

Firms whose profiles of technologicalcompetence are complementary to one another are morelikely to enter into technology-based cooperativeagreements, and a broad level of technologicalcomplementarity is necessary for these agreements toextend as far as a mutual coordination of learningprocesses (combined research ventures). Using data onagreements between the world's largest firms in thearea of information technology (IT) and the patternsof technological specialization of these firms in theIT fields as revealed by their corporate patenting inthe US, we show that the technologicalco-specialization of firms helps to explain allianceformation, over and above the effects of anyco-specialization in IT products. While firms whosetechnological efforts are less complementary are lesslikely to cooperate for technology purposes, if theydo cooperate it is to exploit the differences in theirfields of expertise, and hence they are likely to usequasi-market organizational forms such as licensing,while the purpose of the alliance is restricted to anexchange of knowledge without any joint coordinationof learning (research). Instead, equity jointventures are likeliest when at a broad level ofaggregation the profiles of technologicalspecialization of partners are complementary, but ata more detailed level of disaggregation there is agreater distance between them, such that thecoordination of learning efforts is feasible, butrequires a stronger organizational commitment.     

Testing for Homogeneity in an Exponential Mixture Model

This paper studies diagnostic procedures to test for homogeneity against unobserved heterogeneity in an exponential mixture model. The procedures include a dispersion score test, a likelihood ratio test, a moment likelihood approach and several goodness-of-fit tests. The paper compares the empirical power of these tests on a broad range of alternatives and proposes a new test that combines the dispersion score test with a properly chosen goodness-of-fit procedure; its empirical power comes close to the power of the best of the other tests.     

Frailty models and copulas: similarities and differences

Copulas and frailty models are important tools to model bivariate survival data. Equivalence between Archimedean copula models and shared frailty models, e.g. between the Clayton-Oakes copula model and the shared gamma frailty model, has often been claimed in the literature. In this note we show that, in both the models, there is indeed a well-known equivalence between the copula functions; the modeling of the marginal survival functions, however, is quite different. The latter fact leads to different joint survival functions.     

Inconsistency of the MLE for the Joint Distribution of Interval-Censored Survival Times and Continuous Marks

Abstract.  This paper considers the non-parametric maximum likelihood estimator (MLE) for the joint distribution function of an interval-censored survival time and a continuous mark variable. We provide a new explicit formula for the MLE in this problem. We use this formula and the mark-specific cumulative hazard function of Huang & Louis (1998) to obtain the almost sure limit of the MLE. This result leads to necessary and sufficient conditions for consistency of the MLE, which imply that the MLE is inconsistent in general. We show that the inconsistency can be repaired by discretizing the marks. Our theoretical results are supported by simulations.