The Brier Rule Is not a Good Measure of Epistemic Utility (and Other Useful Facts about Epistemic Betterness)

Measures of epistemic utility are used by formal epistemologists to make determinations of epistemic betterness among cognitive states. The Brier rule is the most popular choice (by far) among formal epistemologists for such a measure. In this paper, however, we show that the Brier rule is sometimes seriously wrong about whether one cognitive state is epistemically better than another. In particular, there are cases where an agent gets evidence that definitively eliminates a false hypothesis (and the probabilities assigned to the other hypotheses stay in the same ratios), but where the Brier rule says that things have become epistemically worse. Along the way to this ‘elimination experiment’ counter-example to the Brier rule as a measure of epistemic utility, we identify several useful monotonicity principles for epistemic betterness. We also reply to several potential objections to this counter-example.     

Extending Standard Models of ZFC to Models of Nonstandard Set Theories

We study those models of ZFCwhich are embeddable, as the class of all standard sets, in a model of internal set theory >ISTor models of some other nonstandard set theories. This revised version was published online in June 2006 with corrections to the Cover Date.     

Some relationships between factors and components

The asymptotic correlations between the estimates of factor and component loadings are obtained for the exploratory factor analysis model with the assumption of a multivariate normal distribution for manifest variables. The asymptotic correlations are derived for the cases of unstandardized and standardized manifest variables with orthogonal and oblique rotations. Based on the above results, the asymptotic standard errors for estimated correlations between factors and components are derived. Further, the asymptotic standard error of the mean squared canonical correlation for factors and components, which is an overall index for the closeness of factors and components, is derived. The results of a Monte Carlo simulation are presented to show the usefulness of the asymptotic results in the data with a finite sample size.The author is indebted to anonymous referees for their comments, corrections and suggestions which have led to the improvement of this article.     

Information matrix estimation procedures for cognitive diagnostic models

Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance.     

Against all odds – is a more differentiated view of personality development in emerging adulthood needed? The case of young apprentices

Personality development in emerging adults who do not attend college after high school has been largely overlooked so far. In this study, we investigated personality development in emerging German adults (N_T1 = 1,886, M_ageT1 = 18.01 years, 29% female) undergoing vocational education and training (VET). The trainees were assessed at the start of VET, 1.5 years later, and another 1.5 years after that, just before graduation. Longitudinal latent change score analyses were applied. Bivariate analyses investigated life satisfaction and job strain as social and work‐related aspects that are potentially reciprocally related to personality development. Mean‐level personality changes included increases in neuroticism and decreases in agreeableness and conscientiousness in the first interval. In the second interval, neuroticism decreased and conscientiousness increased. Simultaneously, trainees reported a gradual decrease in extraversion and openness across the 3‐year time span. Personality, especially agreeableness and conscientiousness, emerged as a stronger predictor of changes in job strain and life satisfaction than vice versa. For example, more agreeable and more conscientious trainees subsequently showed increases in life satisfaction. Trainees reporting higher job strain subsequently showed decreases in agreeableness. Trajectories of personality development partly support the maturity principle that has been established in many college student samples.     

Four Covariance Structure Models for Canonical Correlation Analysis: A COSAN Modeling Approach

The mathematical connection between canonical correlation analysis (CCA) and covariance structure analysis was first discussed through the Multiple Indicators and Multiple Causes (MIMIC) approach. However, the MIMIC approach has several technical and practical challenges. To address these challenges, a comprehensive COSAN modeling approach is proposed. Specifically, we define four COSAN-CCA models to correspond with four possible combinations of the data to be analyzed and the unique parameters to be estimated. In terms of the data, one can analyze either the unstandardized or standardized variables. In terms of the unique parameters, one can estimate either the weights or loadings. Besides the unique parameters of each COSAN-CCA model, all four COSAN-CCA models also estimate the canonical correlations as their common parameters. Taken together, the four COSAN-CCA models provide the correct point estimates and standard error estimates for all commonly used CCA parameters. Two numeric examples are used to compare the standard error estimates obtained from the MIMIC approach and the COSAN modeling approach. Moreover, the standard error estimates from the COSAN modeling approach are validated by a simulation study and the asymptotic theory. Finally, software implementation and future extensions are discussed.     

国际合作中知情同意面临的难题及思考

目前在医学研究的国际合作中,知情同意原则在实施中出现了许多争议和难题.结合一些典型案例,对知情同意的跨文化研究、知情同意表格的误解以及保护受试者与自由研究之间的权衡等问题进行了深入地分析.指出:加强交流、相互尊重、求同存异是解决跨文化研究的必由之路;严格审查、加强监管是避免知情同意流于形式的重要手段;鼓励与防范并举才能达到双赢的局面.     

一个基于综合印象评分法的作文分事后调整模型

对大学英语四、六级考试作文评分进行了详细的描述,重点介绍了作文分的事后调整的原理和方法,并且给出了一个基于线性等值原理的数学推导。认为其数学模型主要是一个运用了“极大似然估计法”和“正态分”概念的统计模型。“评分标准的制定”、“用参照样卷来校准阅卷员对作文评分标准的掌握尺度”以及“阅卷员的培训和考核”构成了大学英语四、六级考试作文信度的基石;而作文分调整中基于“随机分发作文卷”、“客观题分数与作文分相关”以及“评分前后一致性”的统计方法则对出现系统性误差的阅卷员的评分结果进行了事后的校正。还提出如果拥有往次考试总体作文分均值数据,使用“加权移动平均法”可以实现对作文分的跨考次平衡。