Testing equality of two normal covariance matrices with monotone missing data

Abstract

The problem of testing equality of two multivariate normal covariance matrices is considered. Assuming that the incomplete data are of monotone pattern, a quantity similar to the Likelihood Ratio Test Statistic is proposed. A satisfactory approximation to the distribution of the quantity is derived. Hypothesis testing based on the approximate distribution is outlined. The merits of the test are investigated using Monte Carlo simulation. Monte Carlo studies indicate that the test is very satisfactory even for moderately small samples. The proposed methods are illustrated using an example.     

Random effects regression mixtures for analyzing infant habituation

Random effects regression mixture models are a way to classify longitudinal data (or trajectories) having possibly varying lengths. The mixture structure of the traditional random effects regression mixture model arises through the distribution of the random regression coefficients, which is assumed to be a mixture of multivariate normals. An extension of this standard model is presented that accounts for various levels of heterogeneity among the trajectories, depending on their assumed error structure. A standard likelihood ratio test is presented for testing this error structure assumption. Full details of an expectation-conditional maximization algorithm for maximum likelihood estimation are also presented. This model is used to analyze data from an infant habituation experiment, where it is desirable to assess whether infants comprise different populations in terms of their habituation time.     

Politics in evaluation: Politically responsive evaluation in high stakes environments

The role of politics has often been discussed in evaluation theory and practice. The political influence of the situation can have major effects on the evaluation design, approach and methods. Politics also has the potential to influence the decisions made from the evaluation findings. The current study focuses on the influence of the political context on stakeholder decision making. Utilizing a simulation scenario, this study compares stakeholder decision making in high and low stakes evaluation contexts. Findings suggest that high stakes political environments are more likely than low stakes environments to lead to reduced reliance on technically appropriate measures and increased dependence on measures better reflect the broader political environment.     

The African Evaluation Guidelines: 2002. A checklist to assist in planning evaluations, negotiating clear contracts, reviewing progress and ensuring adequate completion of an evaluation

A review of the US ‘program evaluation standards’ (PES), undertaken in a series of workshops and meetings of networks of evaluators in Africa, resulted in modifications to those standards. The result was presented to a plenary session of the Inaugural Conference of the African Evaluation Association in September 1999, attended by over 300 evaluators from 35 countries. The AfrEA Conference decided that a systematic effort should be made to produce a list of African evaluation guidelines, similar to the PES, and that this checklist should be reviewed by national evaluation associations and networks in Africa and field tested in several countries. Ten national and regional networks and associations suggested modifications to the text and endorsed the final version of the guidelines.     

高等数学教学中应用CAI尝试

本文阐明了高等数学自测信息反馈系统的理论内涵 ,介绍了基于数理统计原理制定的新的学生考试成绩评定方法与相应成绩管理软件的基本内容及其在教学实践中的应用功效     

一种新型的GSM接收机的设计与实现

依据GSM协议,结合GSM数字移动通信系统信号传输的特点,给出了基于GSM系统的带软输出结构的MLSE接收机的设计方案,阐述了MLSE接收机的实现算法。实际环境的试验结果表明:工程实现的MLSE接收机具有良好的工作性能和一定的实际应用价值。     

浅析影响因子的局限性

目前大量的机构用论文的被引用率、期刊的影响因子和被 SCI收录的情况作为评价个人、期刊和科研机构之影响力或水平高低的一个重要指标。但却忽略了不同学科的特殊性以及学科的规模、发展速度等非科学的因素对影响因子的局限 ,这就形成了对许多专业的不公平评价 ,因而必须对普通的影响因子加以修正     

晚唐诗歌否定评价的当代反思

从唐末至今 ,论者对晚唐诗大多持否定态度。反思这种带有明显历史惯性的批评现象 ,不难发现 ,不是晚唐诗缺乏思想价值和艺术魅力 ,而是其出现的异于此前诗坛的人生哲学、生活情趣、审美情趣、艺术思维和艺术风格 ,不仅使那些视文学为伦理、政治奴婢的封建文学观念批评者难以认同 ,也使那些对思想文化史发展缺乏认识和分析的批评者 ,难以理解出现在晚唐诗中的种种变化 ,因而导致千余年来的批评失误     

On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models

While much used in practice, latent variable models raise challenging estimation problems due to the intractability of their likelihood. Monte Carlo maximum likelihood (MCML), as proposed by Geyer & Thompson (1992 ), is a simulation-based approach to maximum likelihood approximation applicable to general latent variable models. MCML can be described as an importance sampling method in which the likelihood ratio is approximated by Monte Carlo averages of importance ratios simulated from the complete data model corresponding to an arbitrary value of the unknown parameter. This paper studies the asymptotic (in the number of observations) performance of the MCML method in the case of latent variable models with independent observations. This is in contrast with previous works on the same topic which only considered conditional convergence to the maximum likelihood estimator, for a fixed set of observations. A first important result is that when is fixed, the MCML method can only be consistent if the number of simulations grows exponentially fast with the number of observations. If on the other hand, is obtained from a consistent sequence of estimates of the unknown parameter, then the requirements on the number of simulations are shown to be much weaker.