Model misspecification in proportional hazards regression

The proportional hazards model is frequently used to evaluatethe effect of treatment on failure time events in randomisedclinical trials. Concomitant variables are usually availableand may be considered for use in the primary analyses underthe assumption that incorporating them may reduce bias or improveefficiency. In this paper we consider two approaches to includingcovariate information: regression modelling and stratification.We focus on the setting where covariate effects are nonproportionaland we compare the bias, efficiency and coverage propertiesof these approaches. These results indicate that our intuitionbased on linear model analysis of covariance is misleading.Covariate adjustment in proportional hazards models has littleeffect on the variance but may significantly improve the accuracyof the treatment effect estimator.     

Estimation in regression models for longitudinal binary data with outcome-dependent follow-up

In many observational studies, individuals are measured repeatedly over time, although not necessarily at a set of pre-specified occasions. Instead, individuals may be measured at irregular intervals, with those having a history of poorer health outcomes being measured with somewhat greater frequency and regularity. In this paper, we consider likelihood-based estimation of the regression parameters in marginal models for longitudinal binary data when the follow-up times are not fixed by design, but can depend on previous outcomes. In particular, we consider assumptions regarding the follow-up time process that result in the likelihood function separating into two components: one for the follow-up time process, the other for the outcome measurement process. The practical implication of this separation is that the follow-up time process can be ignored when making likelihood-based inferences about the marginal regression model parameters. That is, maximum likelihood (ML) estimation of the regression parameters relating the probability of success at a given time to covariates does not require that a model for the distribution of follow-up times be specified. However, to obtain consistent parameter estimates, the multinomial distribution for the vector of repeated binary outcomes must be correctly specified. In general, ML estimation requires specification of all higher-order moments and the likelihood for a marginal model can be intractable except in cases where the number of repeated measurements is relatively small. To circumvent these difficulties, we propose a pseudolikelihood for estimation of the marginal model parameters. The pseudolikelihood uses a linear approximation for the conditional distribution of the response at any occasion, given the history of previous responses. The appeal of this approximation is that the conditional distributions are functions of the first two moments of the binary responses only. When the follow-up times depend only on the previous outcome, the pseudolikelihood requires correct specification of the conditional distribution of the current outcome given the outcome at the previous occasion only. Results from a simulation study and a study of asymptotic bias are presented. Finally, we illustrate the main results using data from a longitudinal observational study that explored the cardiotoxic effects of doxorubicin chemotherapy for the treatment of acute lymphoblastic leukemia in children.     

小型猪胰腺移植急性排斥反应模型的实验研究

目的　建立小型猪胰腺移植动物模型 ,探索早期诊断急性排斥反应的方法。方法　 4 0只猪随机配对行胰腺移植 2 0次 ,将供胰所带的血管与受体髂血管吻合 ,所带小段十二指肠与空肠吻合 ,术中监测平均动脉压、中心静脉压及血气。术后测定受体的血淀粉酶、血糖 ,监测外周血免疫指标 ,彩色多普勒检测供胰血流及超声引导下活检、组织病理检查。结果　移植手术成功率为 90 % ,受体平均动脉压在吻合血管开放后有明显下降 ,与血流开放前差异有显著性 (P <0 0 5 ) ,输血有助于手术成功 ,受体术后平均存活 (12 6± 2 3)d。外周血免疫学监测指标早于供胰的组织病理改变 ,两者的改变均早于急性排斥反应的临床表现。结论　小型猪适用于胰腺移植模型的建立 ,加强术中循环功能的管理、及时输血有利于受体成活 ;超声引导下穿刺活检供胰的组织病理学检查与监测外周血免疫指标均适于早期诊断急性排斥反应     

高脂高糖饮食结合链脲佐菌素建立2型糖尿病大鼠模型的改良

目的对目前常用的高脂高糖饮食结合链脲佐菌素建（STZ）建立2型糖尿病大鼠模型的方法进行改良。方法选择40只雄性SD幼鼠,对传统方法进行改良。改良的方法包括：1.采用幼鼠（4周龄）造模;2.用实验方法确定STZ致糖尿病的亚致病剂量;3.大鼠生化指标检测根据用血量不同采取尾静脉、尾动脉和摘除眼球取血等多种取血方式。结果实验组大鼠血糖明显升高（13.7±1.57 mmol/L）。大鼠肝脏、胰腺、脑组织和肾脏等多个器官出现了病变,实验大鼠生存时间较长（9个月以上）。结论本研究完善了2型糖尿病的建模方法。     

Optimum Designs for Estimating the Variance Components in a Simple Variance Component Model (Model II), I

The methods of optimal designing of experiments proposed by WALD (1943) are used for determination of an A_σ2-optimal concrete design for estimation of σ^2′ = (σ, σ) in case of one-way analysis of variance. Starting point of definition of the optimality criterion is a quadratic loss matrix.     

改良线栓法大鼠大脑中动脉阻塞模型的建立

目的对大鼠大脑中动脉阻塞（MCAO）再灌注模型进行改良,通过比较再灌注24h时大鼠神经功能评分、梗死率、模型制作时间、成功率和死亡率等指标评价改良线栓法大鼠MCAO再灌注模型的有效性。方法12只SD大鼠随机分为对照和模型两组,对照组采用分离结扎翼腭动脉,从颈外动脉插入线栓至大脑中动脉。模型组采用不分离结扎翼腭动脉,从颈总动脉分叉处插入线栓至大脑中动脉。阻断大脑中动脉血供2h后将线栓拔出实现再灌注。于再灌注24h时观察脑组织组织病理学改变,计算比较两组大鼠神经功能评分、模型制作时间、模型成功率和死亡率以及鼠脑切片TTC染色测量脑梗死率。结果两组MCAO模型在再灌注24h后大鼠神经功能评分、梗死率、模型成功率和死亡率等方面没有显著差异;模型组的模型制作时间显著少于对照组（P〈0．05）。结论采用不分离结扎翼腭动脉,由颈总动脉插入线栓的改良线栓法是稳定和可靠的MCAO造模方法。     

Evaluation of the Kullback-Leibler Discrepancy for Model Selection in Open Population Capture-Recapture Models

The objective of this paper is to introduce the logical basis of AIC-based model selection to persons analyzing capture-recapture data and to explore the key theorettical aspect of AIC based model selection, for open-model capture-recapture, needed for AIC to perform well in this context. Almost all previous work on AIC assumes a Gaussian model; that assumption does not hold for capture-recapture models. Assuming the Cormack-Jolly-Seber model as the true model, we used numerical methods to evaluate the expectation of the log-likelihood relative to Akaike's target predictive log-likelihood. The use of this particular target criterion was motivated by the idea of using the Kullback-Leibler discrepancy for model selection, for which Akaike found the bias of the sample log-likelihood was asymptotically K, where K = the number of estimated (by MLE) parameters. In some sense, then, AIC is a bias-adjusted log-likelihood. For a set of 81 plausible cases, we evaluated this bias almost exactly. The ratio of this bias to the first order theory (bias of K) and to second order theory (K + a sample size adjustment) is essentially 1 for these 81 cases. Thus, AIC should be a suitable basis for model selection in open model capture-recapture.     

对虾白斑综合征杆状病毒体内增殖模型的建立

应用对虾白斑综合征杆状病毒（WSSV）,对淡水克氏螯虾、罗氏沼虾、日本沼虾和两种淡水蟹（中华绒螯蟹、长江华溪蟹）进行人工感染实验。结果除淡水克氏螯虾之外,其它受试的虾蟹均不能感染WSSV。克氏螯虾3个不同剂量级感染至12d平均死亡率为94％。从发病或死亡个体采集血淋巴,经电镜负染色可观察到完整的病毒粒子,其形态大小、靶细胞组织病理均与从中国对虾中分离的WSSV相似或相同。同时,通过原位杂交技术进一步证明该实验的可靠性。克氏螯虾重复感染效果良好,有可能成为研究WSSV的一种理想的病毒体内增殖模型。     

The Residual Likelihood Ratio Test for the Variance Ratio in a Linear Model with Two Variance Components

Residual maximum likelihood has proved to be a successful approach to the estimation of variance components. In this paper, its counterpart in testing, the residual likelihood ratio test, is applied to testing the ratio of two variance components. The test is compared with the Wald test and the locally most powerful invariant test.     

虎源H5N1亚型禽流感病毒感染小鼠模型的建立

为研究H5N1亚型禽流感病毒的病原特性、致病机理及对其疫苗与救治药物效果评价提供平台,利用本室分离鉴定的虎源A/Tiger/Harbin/01/2002株(简称HAB/01)H5N1亚型禽流感病毒进行连续10倍稀释后,对4～6周龄雄性BALB/c小鼠经乙醚麻醉后进行滴鼻攻毒,每个稀释度接种10只实验小鼠,测定其MLD50,检测小鼠感染、致病的多项指标,观察期为14d。结果感染小鼠呈现出规律的以肺炎为主的临床症状、病理变化及病死率;测得该病毒对小鼠的MLD50为10-7.1/0.05mL。成功建立了虎源H5N1亚型禽流感病毒感染BALB/c小鼠的实验模型。     

Model diagnostic tests for selecting informative correlation structure in correlated data

In the generalized method of moments approach to longitudinaldata analysis, unbiased estimating functions can be constructedto incorporate both the marginal mean and the correlation structureof the data. Increasing the number of parameters in the correlationstructure corresponds to increasing the number of estimatingfunctions. Thus, building a correlation model is equivalentto selecting estimating functions. This paper proposes a chi-squaredtest to choose informative unbiased estimating functions. Weshow that this methodology is useful for identifying which sourceof correlation it is important to incorporate when there aremultiple possible sources of correlation. This method can alsobe applied to determine the optimal working correlation forthe generalized estimating equation approach.     

具有亲缘关系矩阵的混合模型的方差组分迭代估计——应用于计算BLUP的方差比值和遗传参数

论述的是来自非均街资料的混合模型中具有亲缘关系矩阵时利用迭代法估计方差组分问题。这篇文章表明计算程序是可行的,只要能够按照混合模型中固定效应的结构矩阵和Henderson方法3的固定效应的假设条件正确地计算二次型约化平方和,就可获得较为精确的方差组分估计值;而且表明方差初始比值k偏高或偏低,不影响迭代求解的最后结果,这是因为在迭代过程中可以通过结构矩阵x'x和x'x的控制而自行调整。这些方差组分不仅可应用于选种种畜用的BLUP计算,还可用来估计遗传参数。