Performance of traditional f tests in repeated measures designs under covariance heterogeneity

This study investigates the performance of two traditional F tests, one for main effects and the other for interaction in repeated measures designs under several conditions of covariance heterogeneity. Overall, the test for interaction is more vulnerable than the one for main effects. Distortion in the level of significance is less serious for the case of equal group size.     

An asymptotic distribution-free selection procedure for a two-way layout problem

This paper deals with an asymptotic distribution-free subset selection procedure for a two-way layout problem. The treatment effect with the largest unknown value is of interest to us. The block effect is a nuisance parameter in this problem. The proposed procedure is based on the Hodges-Lehmann estimators of location parameters. The asymptotic relative efficiency of the proposed procedure with the normal means procedure is evaluated. It is shown that the proposed procedure has a high efficiency.     

Repeated measurements designs - a review

Any experiment in which one or more of the experimental units is used more than once is called a repeated measurements experiment. The associated design of a repeated measurements experiment is referred to as a repeated measurements design. This review covers some known results on repeated measurements designs. Emphasis is placed on the impact of optimal design theory. Some construction methods for these designs are presented. Hedayat and Afsarinejad (1975) has an extensive bibliography of earlier literature. A bibliography of these designs published after 1974 is provided at the end of this paper.     

Goodness of fit for thei ordered categories discrete uniform distribution

Goodness of fit for thei ordered categories discrete uniform distribution can be carried out using Pearson's X² _pstatistic and its components. Applications of this technique are considered and comparisons made with recently suggested empirical uniform distribution     

MODELING THE LIFETIME OF LONGITUDINAL ELEMENTS

In the study of the stochastic behaviour of the lifetime of an element as a function of its length, it is often observed that the failure time (or lifetime) decreases as the length increases. In probabilistic terms, such an idea can be expressed as follows. Let T be the lifetime of a specimen of length x, so the survival function, which denotes the probability that an element of length x survives till time t, will be given by S_T (t, x) = P(T > t/α(x), where α(x) is a monotonically decreasing function. In particular, it is often assumed that T has a Weibull distribution. In this paper, we propose a generalization of this Weibull model by assuming that the distribution of T is Generalized gamma (GG). Since the GG model contains the Weibull, Gamma and Lognormal models as special and limiting cases, a GG regression model is an appropriate tool for describing the size effect on the lifetime and for selecting among the embedded models. Maximum likelihood estimates are obtained for the GG regression model with α(x) = cx^b . As a special case this provide an alternative to the usual approach to estimation for the GG distribution which involves reparametrization. Related parametric inference issues are addressed and illustrated using two experimental data sets. Some discussion of censored data is also provided.     

A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.     

高等教育投资回报率估算：基于西部三个城市的微观数据

本文基于中国西部三个城市,7949个住户的微观数据,利用内生的处理效应模型测算了城市家庭20-35岁青年的高等教育投资回报率。经验研究的结果显示：1. 现阶段青年人的高等教育投资内部报酬率大致在7%左右;按照30年工作时间计算的收入增加现值大约在8万元上下,高等教育使得月收入期望值平均增加80%。高等教育还能够使青年就业的可能性增加8%左右;2. 从性别的视角观察,高等教育对于女性的回报率高于男性,女青年内部报酬率大约在8.3%（男青年7.6%）;就业概率增加15.9%（男青年4%）,每月工资期望值增加122%（男青年67.5%）;3. 如果高等教育的全部花费增加到平均6万元,则从单纯的现金流意义上说,高等教育没有增加收入的价值了。     

集聚效应、集聚效率与城市规模分布变化

摘　　要:本文从城市集聚效应的视角,分析我国城市规模分布的结构性变化的机制,在此基础上构建了包含集聚效应的城市总量生产函数的计量经济学模型,然后应用OLS方法估算我国不同规模等级城市的平均集聚效应指数和平均集聚效率指数．并对比分析其对城市规模分布变化的影响。本文的实证结果表明,平均集聚效率指数的高低与城市规模分布比重的增减相一致。     

我国生产用能源消费变动的分解分析

摘　　要:能源消费分解是探讨能源消费变动影响因素的一种常用方法。在本文中介绍了目前研究中较为合理的一种分解方法——对数平均D氏指数法,并借助这一方法来对我国“六五”时期以来的生产用能源消费情况进行分解分析,探讨产业结构变动和产业内效率提高对能源消费和总体单位能耗的影响。根据测算结果,笔者认为产业内能源效率的提高是我国能源节约的主要因素;进一步建议政府构建“能源分解指数体系”作为制定能源政策的依据。