一种模型模拟结果的统计检验方法

模拟结果的准确性是衡量生态学模型是否成功的关键,但采用统计学方法判别模型模拟结果与观察值相符程度的报道较少。根据两个直线回归方程能否合并为一个方程的统计学检验方法,提出了通过检验观察值与模拟值直线回归方程和1∶1直线方程截距与斜率是否相同,进而在统计显著水平上判断生态学模型模拟值与观察值一致性的统计学检验方法。数据检验表明,此方法可以较好解决判断生态学模型模拟结果准确性的问题。     

The Wald Statistic in Proportional Hazards Hypothesis Testing

In survivorship modelling using the proportional hazards model of Cox (1972, Journal of the Royal Statistical Society, Series B, 34, 187–220), it is often desired to test a subset of the vector of unknown regression parameters β in the expression for the hazard rate at time t. The likelihood ratio test statistic is well behaved in most situations but may be expensive to calculate. The Wald (1943, Transactions of the American Mathematical Society 54, 426–482) test statistic is easier to calculate, but has some drawbacks. In testing a single parameter in a binomial logit model, Hauck and Donner (1977, Journal of the American Statistical Association 72, 851–853) show that the Wald statistic decreases to zero the further the parameter estimate is from the null and that the asymptotic power of the test decreases to the significance level. The Wald statistic is extensively used in statistical software packages for survivorship modelling and it is therefore important to understand its behavior. The present work examines empirically the behavior of the Wald statistic under various departures from the null hypothesis and under the presence of Type I censoring and covariates in the model. It is shown via examples that the Wald statistic's behavior is not as aberrant as found for the logistic model. For the single parameter case, the asymptotic non-null distribution of the Wald statistic is examined.     

Testing homogeneity in Weibull-regression models

In survival studies with families or geographical units it may be of interest testing whether such groups are homogeneous for given explanatory variables. In this paper we consider score type tests for group homogeneity based on a mixing model in which the group effect is modelled as a random variable. As opposed to hazard-based frailty models, this model presents survival times that conditioned on the random effect, has an accelerated failure time representation. The test statistics requires only estimation of the conventional regression model without the random effect and does not require specifying the distribution of the random effect. The tests are derived for a Weibull regression model and in the uncensored situation, a closed form is obtained for the test statistic. A simulation study is used for comparing the power of the tests. The proposed tests are applied to real data sets with censored data.     

Analysis of Repeated Measurements with Ante-Dependence Covariance Models

This paper considers the use of ante-dependence models in problems with repeated measures through time. These are conditional regression models which reflect the dependence of a measure on some of the previous observations from the same subject. We present maximum likelihood estimators of the covariance matrix and procedures for selecting the order of ante-degendence based on penalized like-lihoods. Extensions to missing data situations are discussed. We propose Wald-type test statistics and apply them in two situations common in experiments with repeated measures: one with pre-study observations and another one with small sample size relative to the number of time periods. In these examples, tests assuming ante-dependence find effects which are not detected using competing procedures.     

The use of score tests for inference on variance components

Whenever inference for variance components is required, the choice between one-sided and two-sided tests is crucial. This choice is usually driven by whether or not negative variance components are permitted. For two-sided tests, classical inferential procedures can be followed, based on likelihood ratios, score statistics, or Wald statistics. For one-sided tests, however, one-sided test statistics need to be developed, and their null distribution derived. While this has received considerable attention in the context of the likelihood ratio test, there appears to be much confusion about the related problem for the score test. The aim of this paper is to illustrate that classical (two-sided) score test statistics, frequently advocated in practice, cannot be used in this context, but that well-chosen one-sided counterparts could be used instead. The relation with likelihood ratio tests will be established, and all results are illustrated in an analysis of continuous longitudinal data using linear mixed models.     

Testing approaches for overdispersion in poisson regression versus the generalized poisson model

Overdispersion is a common phenomenon in Poisson modeling, and the negative binomial (NB) model is frequently used to account for overdispersion. Testing approaches (Wald test, likelihood ratio test (LRT), and score test) for overdispersion in the Poisson regression versus the NB model are available. Because the generalized Poisson (GP) model is similar to the NB model, we consider the former as an alternate model for overdispersed count data. The score test has an advantage over the LRT and the Wald test in that the score test only requires that the parameter of interest be estimated under the null hypothesis. This paper proposes a score test for overdispersion based on the GP model and compares the power of the test with the LRT and Wald tests. A simulation study indicates the score test based on asymptotic standard Normal distribution is more appropriate in practical application for higher empirical power, however, it underestimates the nominal significance level, especially in small sample situations, and examples illustrate the results of comparing the candidate tests between the Poisson and GP models. A bootstrap test is also proposed to adjust the underestimation of nominal level in the score statistic when the sample size is small. The simulation study indicates the bootstrap test has significance level closer to nominal size and has uniformly greater power than the score test based on asymptotic standard Normal distribution. From a practical perspective, we suggest that, if the score test gives even a weak indication that the Poisson model is inappropriate, say at the 0.10 significance level, we advise the more accurate bootstrap procedure as a better test for comparing whether the GP model is more appropriate than Poisson model. Finally, the Vuong test is illustrated to choose between GP and NB2 models for the same dataset.     

家畜试验中的一种相关扰动回归模型

本文根据数量遗传学原理,从家畜群体中同一家系内的个体之间存在的遗传相关性出发,建立了扰动项相关的回归模型,运用回归理论讨论一类相关样本的统计推断及其应用。     

Prediction of the preservation of freeze-dried cucumber mosaic virus

A mathematical model to predict the outcome of preserving plant viruses has been developed. The survival of two cucumber mosaic virus strains lyophilized in leaves and in protected plant sap was evaluated using an accelerated storage test at 28, 37 and 45°C. The combinations of 5% (w/v) sorbitol and 7% (w/v) glucose with 3.6% (w/v) dextran 40000 were applied as protecting media. The predicted values to a great extent correspond to the experimental data, achieved after 1, 4 and 7 years of storage.     

探索以“霍乱弧菌检测虚拟仿真实验”为载体的混合式实验教学模式

虚拟仿真实验是一种现代信息化和智慧教学的重要方法,对高等医学院校教学质量的发展起到重要的推进作用。我们自主开发建设的“霍乱弧菌检测与防控虚拟仿真实验”,既弥补了因生物安全问题不能开展的实验教学,也解决了微生物学检验实验教学中存在的操作标准化问题。采用“三步进阶”混合教学模式,实现以“学生为中心”的师生互动模式,创建“设计性实验报告”,与育人元素有机结合,培育医学生的职业使命感。细化考核标准,实现过程性评价。探索课前启发铺垫、课中内化升华、课后巩固拓展混合式实验教学模式,有效提高学生的实验技能,实现知行合一、素能共育的教学目标。     

Likelihood-ratio tests for hidden Markov models

We consider hidden Markov models as a versatile class of models for weakly dependent random phenomena. The topic of the present paper is likelihood-ratio testing for hidden Markov models, and we show that, under appropriate conditions, the standard asymptotic theory of likelihood-ratio tests is valid. Such tests are crucial in the specification of multivariate Gaussian hidden Markov models, which we use to illustrate the applicability of our general results. Finally, the methodology is illustrated by means of a real data set.     

A convenient screening test system and a model for thermal germination responses of wild plant seeds: behaviour of model and real seeds in the system

Abstract A convenient test system for screening the thermal germination behaviour of seeds was developed for both basic and applied research in seed germination ecophysiology. Only two temperature-controlled facilities, a test period of about a month and a relatively small number of sample seeds arc needed to obtain information on the thermal-germination parameters of individual seed populations, such as lower or higher limit temperatures, and thermal times required for germination. In the test system, the germination performances of sample seed populations were compared under two temperature regimes: a gradually increasing temperature regime and a gradually decreasing temperature regime, in which the seeds were subjected to gradually changing temperatures in the range of 4 36°C. In order to assess the effects of various values for thermal-germination parameters on the patterns of germination performance in the system, the behaviour of model seeds characterized by a definite set of thermal germination parameters were investigated. Referring to the results of the simulations, the actual germination patterns of some wild-seed populations in the test system were interpreted in terms of thermal-germination parameters.     

A Unifying,Analytic Model for Certain Linear Rank Tests. Part II: Exact Distribution Algorithms

On the basic of the analytic properties of the unifying model developed in the earlier Part I of this presentation, exact distribution algorithms are developed for the Wilcoxon 2-sample sum-of-rank test, the Freund-Ansari scale test, and the Wilcoxon signed-rank test. For the signed-rank test, provisions are made for zero-differences.     

Bayesian Meta‐Analysis of the Accuracy of a Test for Tuberculous Pleuritis in the Absence of a Gold Standard Reference

Summary Absence of a perfect reference test is an acknowledged source of bias in diagnostic studies. In the case of tuberculous pleuritis, standard reference tests such as smear microscopy, culture and biopsy have poor sensitivity. Yet meta‐analyses of new tests for this disease have always assumed the reference standard is perfect, leading to biased estimates of the new test’s accuracy. We describe a method for joint meta‐analysis of sensitivity and specificity of the diagnostic test under evaluation, while considering the imperfect nature of the reference standard. We use a Bayesian hierarchical model that takes into account within‐ and between‐study variability. We show how to obtain pooled estimates of sensitivity and specificity, and how to plot a hierarchical summary receiver operating characteristic curve. We describe extensions of the model to situations where multiple reference tests are used, and where index and reference tests are conditionally dependent. The performance of the model is evaluated using simulations and illustrated using data from a meta‐analysis of nucleic acid amplification tests (NAATs) for tuberculous pleuritis. The estimate of NAAT specificity was higher and the sensitivity lower compared to a model that assumed that the reference test was perfect.     

用一个相对简单的方法来探测核苷酸替代模型的异质性

对于可观察到的分子序列进化模型的不同,提出一个相对简单的方法——卡方检测,来检测在DNA序列间替代过程的同质性。这个卡方检测方法不管在座位间下列3个条件是否满足皆是成立的：（1）替代率的异质性;（2）进化率／模型的相关性;（3）替代模型的变异。计算机模拟也显示出卡方检测在各种生物学条件下的序列进化模型是非常有效的。在真实数据中,11种节肢动物线粒体DNA的比较中发现,水蚤或卤虫与其他9种节肢动物以高百分比违背了同质性进化模型假设,显然是由于AT含量高而引起的,且在两种蚊子的线粒体DNA比较中发现,其满足同质性假设仅有7．69％。还比较了卡方淦测与Kumar and Gadagkar的ID检测之间的效能差异：在较为复杂的模型下,卡方检测效率在许多情况下较ID检测方法略高;并且在犯Ⅰ-型错误以及卡方测验的效率曲线中清楚地表明我们的方法是保守的,而Kumar等的方法是不保守的。