Goodness-of-fit tests of generalized linear mixed models for repeated ordinal responses

Categorical longitudinal data are frequently applied in a variety of fields, and are commonly fitted by generalized linear mixed models (GLMMs) and generalized estimating equations models. The cumulative logit is one of the useful link functions to deal with the problem involving repeated ordinal responses. To check the adequacy of the GLMMs with cumulative logit link function, two goodness-of-fit tests constructed by the unweighted sum of squared model residuals using numerical integration and bootstrap resampling technique are proposed. The empirical type I error rates and powers of the proposed tests are examined by simulation studies. The ordinal longitudinal studies are utilized to illustrate the application of the two proposed tests.     

空间面板杜宾模型的Bootstrap Wald-COMFAC检验研究

将共同因子约束(COMFAC)的Wald检验问题引入到空间面板模型中,讨论空间面板杜宾模型与空间面板误差模型的识别问题。蒙特卡洛模拟表明:在有限样本下,基于渐近临界值的Wald检验有着良好的检验功效,但存在着较为严重的尺度扭曲。进一步采用残差Bootstrap方法,在不损失检验功效的前提下,能够显著地降低检验的尺度扭曲。因此,残差Bootstrap方法是更为有效的检验方法。     

Accurate estimation for extra-Poisson variability assuming random effect models

In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.     

Confidence intervals based on the deviance statistic for the hyperparameters in state space models

The main objective of this work is to evaluate the performance of confidence intervals, built using the deviance statistic, for the hyperparameters of state space models. The first procedure is a marginal approximation to confidence regions, based on the likelihood test, and the second one is based on the signed root deviance profile. Those methods are computationally efficient and are not affected by problems such as intervals with limits outside the parameter space, which can be the case when the focus is on the variances of the errors. The procedures are compared to the usual approaches existing in the literature, which includes the method based on the asymptotic distribution of the maximum likelihood estimator, as well as bootstrap confidence intervals. The comparison is performed via a Monte Carlo study, in order to establish empirically the advantages and disadvantages of each method. The results show that the methods based on the deviance statistic possess a better coverage rate than the asymptotic and bootstrap procedures.     

Conditional design of the EWMA median chart with estimated parameters

The exponentially weighted moving average (EWMA) chart is often designed assuming the process parameters are known. In practice, the parameters are rarely known and need to be estimated from Phase I samples. Different Phase I samples are used when practitioners construct their own control chart's limits, which leads to the “Phase I between-practitioners” variability in the in-control average run length (ARL) of control charts. The standard deviation of the ARL (SDARL) is a good alternative to quantify this variability in control charts. Based on the SDARL metric, the performance of the EWMA median chart with estimated parameters is investigated in this paper. Some recommendations are given based on the SDARL metric. The results show that the EWMA median chart requires a much larger amount of Phase I data in order to reduce the variation in the in-control ARL up to a reasonable level. Due to the limitation of the amount of the Phase I data, the suggested EWMA median chart is designed with the bootstrap method which provides a good balance between the in-control and out-of-control ARL values.     

当代先锋文学中的江南文化因素

江南文化的诗性特征和在全国文化版图中得天独厚的领先优势,是当今中国先锋文学的深厚精神和艺术营养。与伦理的北方齐鲁文化以及同处南方的其他文化类型相比,江南文化的审美性带有了某种宗教般的超越性品格。这些深厚的文化积淀在当代先锋文学之中,成为这种新潮审美形式不竭的精神和艺术资源。然而这种继承和吸纳是以一种悖反的方式实现的。     

心律波动信号的1/f噪声特性分析

心律波动信号具有1/f噪声特性,是非平稳的。该文采用平均功率谱密度方法,分析了基于平均功率谱密度和最小二乘拟合法求正常人和心脏充血患者的心律波动信号的谱参数,发现根据谱参数可以定量地区分正常人与心脏充血患者:大部分正常人的心律波动信号的谱参数大于1,而大部分心脏充血患者的心律波动信号的谱参数小于1,该结论可为心脏病的诊断与预诊断提供一种辅助手段。     

论语言变体和语用失误之间的互相影响

第二语言习得的过程是一个自然的连续体。语言变体研究第二语言习得过程中连续体的节．属于语言习得过程的输入。语言变体由系统变体和非系统变体构成,其中又含有个体变体和语境变体。语用失误则将研究的重点放在语用上,注重语言使用者运用语言过程中出现的失误,属于语言交际过程中的输出。语用失误由语用语言失误和社会语用失误构成。两种不同的理论研究共同的对象——语言习得者,从不同的角度来研究语言的习得和使用,这就极大地丰富了语言习得和使用的内涵,对语言的学和教有着十分重要的价值。     

Modelling udder infection data using copula models for quadruples

We study copula models for correlated infection times in the four udder quarters of dairy cows. Both a semi-parametric and a nonparametric approach are considered to estimate the marginal survival functions, taking into account the effect of a binary udder quarter level covariate. We use a two-stage estimation approach and we briefly discuss the asymptotic behaviour of the estimators obtained in the first and the second stage of the estimation. A pseudo-likelihood ratio test is used to select an appropriate copula from the power variance copula family that describes the association between the outcomes in a cluster. We propose a new bootstrap algorithm to obtain the p-value for this test. This bootstrap algorithm also provides estimates for the standard errors of the estimated parameters in the copula. The proposed methods are applied to the udder infection data. A small simulation study for a setting similar to the setting of the udder infection data gives evidence that the proposed method provides a valid approach to select an appropriate copula within the power variance copula family.     

Increasing Vocal Variability in Children with Autism Using a Lag Schedule of Reinforcement

Variability has been demonstrated to be an operant dimension of behavior (Neuringer, 2002; Page & Neuringer, 1985). Recently, lag schedules have been used to demonstrate operant variability of verbal behavior in persons with a diagnosis of autism (e.g., Lee, McComas, & Jawor, 2002). The current study evaluated the effects of a Lag 1 schedule on the vocal variability of 2 nonverbal children with a diagnosis of autism. Results showed systematic increases in variability during the Lag 1 schedule. Implications of lag schedules for speech and language training are discussed.