Analysis of binary data in the randomized complete block design

The technique proposed by Shah and Claypool (1984) is extended here for the randomized complete block design with one binary observation per cell. In addition, it provides an al- ternative derivation of the distribution of Cochran's Q sta- tistic which is straightforward.     

A bayesian approach to prediction in analysis of variance settings

This paper takes the results of Lindley and smith ( 1972 ) one step further, by finding the predictive distribution of an observation y^* whose distribution is normal, and centred at A^* ₁θ₁ We then apply this distribution to the case of prediction based on data obtained in one and two wau ANOVA situations. For Example, it turns out that for two way ANOVA with interaction, the predictive mean, (which we would use as the predictor) is a weighted combination of sample main effects and interaction effects     

Predicting early educational program placement with discrete discriminant analysis

The purpose of this study was to predict placement and nonplacement outcomes for mildly handicapped three through five year old children given knowledge of developmental screening test data. Discrete discriminant analysis (Anderson, 1951; Cochran & Hopkins, 1961; Goldstein & Dillon, 1978) was used to classify children into either a placement or nonplacement group using developmental information retrieved from longitudinal Child Find records (1982-89). These records were located at the Florida Diagnostic and Learning Resource System (FDLRS) in Sarasota, Florida and provided usable data for 602 children. The developmental variables included performance on screening test activities from the Comprehensive Identification Process (Zehrbach, 1975), and consisted of: (a) gross motor skills, (b) expressive language skills, and (c) social-emotional skills. These three dichotomously scored developmental variables generated eight mutually exclusive and exhaustive combinations of screening data. Combined with one of three different types of cost-of-misclassification functions, each child in a random cross-validation sample of 100 was classified into one of the two outcome groups minimizing the expected cost of misclassification based on the remaining 502 children. For each cost function designed by the researchers a comparison was made between classifications from the discrete discriminant analysis procedure and actual placement outcomes for the 100 children. A logit analysis and a standard discriminant analysis were likewise conducted using the 502 children and compared with results of the discrete discriminant analysis for selected cost functions.     

赛珍珠等欧美人的看法对文学经典观的启示——中外文学经典标准的实际差异与对策纵横谈

中外学术界在文学经典观上看似达成了统一,但其实二者之间还存在实际操作层面的诸多差异.比较赛珍珠等欧美人与中国某些学者对文学的识见,可以看出中外在古典文学与现当代文学经典衡量上的差异,也可看出中国学者执行的文学经典标准普遍偏高,中外在文学经典标准实际操作层面有较大的差异.文学研究者应适当降低标准,进行文学经典扩容,将经典分类分得更细一些,适当宽容地对待文学作品的缺憾,同时文学经典也可走民族文化型的道路.     

洞庭渔歌的界定及其分类研究

洞庭渔歌作为一个歌种,其文化内涵已经超越了一个区域音乐歌曲种类的边界,成为一个地方音乐文化的标签。从歌曲概念扩展到歌舞、舞蹈、文学剧本的名称,其意义已经不是一个区域歌曲的统称,而是一个区域文化的美学象征。要理解洞庭渔歌,必须从日常生活和学术研究两个层面理解,必须从广义和狭义两个方面给予界定,从多方面进行分类研究,理清其历史的边界和当下的使用范围,让本区域之外的人,历史地了解和理解这一区域音乐文化概念,研究洞庭渔歌的概念及其分类主要是为了确立其研究范畴,划定研究疆域,理清审美界限,推进洞庭渔歌研究走向深化、细化、科学化。     

新中国成立以来西南地区民族识别研究概述

我国西南地区少数民族众多,因此,民族识别的主要任务其实是对西南地区的少数民族进行识别。总体来讲,新中国成立以来西南地区的民族识别研究经历了从政府主导到学术探讨两个大的阶段。政府主导阶段的民族识别主要是在大规模的民族调查基础上进行的,同时在民族识别的依据坚持了科学标准与民族意愿并重的原则,而且日益向后者倾斜。而学术探讨阶段首先对之前西南地我的民族识别工作进行了回顾与反思,进一步集中讨论了西南地区待识别民族的族属问题、族群认同问题,并对西方学者解构中国西南地区民族识别的观点进行回应与讨论。西南民族识别的研究未来还需在理论评价、族属遗留、“56个民族”框架下西南民族的演变等问题上进行深入研究。     

Measuring exposure to bullying at work: The validity and advantages of the latent class cluster approach

Abstract

This paper addresses the construct and predictive validity of two methods for classifying respondents as victims of workplace bullying. Although bullying is conceived as a complex phenomenon, the dominant method used in bullying surveys, the operational classification method, only distinguishes two groups: victims versus non-victims. Hence, the complex nature of workplace bullying may not be accounted for. Therefore a latent class cluster approach is suggested to model the data, which was obtained by using the Negative Acts Questionnaire (NAQ) administered to employees in Belgium (n=6,175). Latent class modelling is a method of analysis that does not appear to have been used in occupational health psychology before. In this study, six latent classes emerged: “not bullied,” “limited work criticism,” “limited negative encounters,” “sometimes bullied,” “work related bullied,” and “victims.” The results show that compared to the traditional operational classification method, the latent class cluster approach shows higher construct and higher predictive validity with respect to self-assessments and indicators of strain and well-being at work. The consequences of these results for theory, future research, and practice are discussed.     

Inverting covariance matrices in unbalanced hierarchical models ∗

Explicit expression for the inverse of the covariance matrix in a linear experiment with unbalanced multiway hierarchical classification of the random effects is obtained.