A Measure for the Reliability of a Rating Scale Based on Longitudinal Clinical Trial Data

A new measure for reliability of a rating scale is introduced, based on the classical definition of reliability, as the ratio of the true score variance and the total variance. Clinical trial data can be employed to estimate the reliability of the scale in use, whenever repeated measurements are taken. The reliability is estimated from the covariance parameters obtained from a linear mixed model. The method provides a single number to express the reliability of the scale, but allows for the study of the reliability’s time evolution. The method is illustrated using a case study in schizophrenia. The authors are grateful to J&J PRD for kind permission to use their data. We gratefully acknowledge support from the Belgian IUAP/PAI network “Statistical Techniques and Modeling for Complex Substantive Questions with Complex Data.”     

我国公务员绩效评估公平性结构的实证研究

本论文以833名公务员为对象,通过构建公务员绩效评估公平性问卷,对公务员绩效评估公平性的结构进行了探讨。探索性因素分析表明,公务员绩效评估公平性的结构主要包括评估系统公平、评估者公平、信息公平和人际公平等四个维度;验证性因素分析表明问卷,具有较好的构思效度和建构信度,其问卷可以作为测量公务员绩效评估公平性的工具。     

多重情绪智力量表(MEIS)的信度、结构效度及应用评价研究

对多重情绪智力量表（MEIS）的信度和结构效度进行了实证检验,结果发现,MEIS的内部一致性信度（a）系数偏低,各分量表的分半信度系数很低;MEIS总量表的结构效度明显不足,对七个分量表的因素分析结果显示,每个维度对总量表的贡献率很低;无法满足Mayer和Salovey情绪智力4维度理论框架。对4个维度逐一进行二阶因素分析结果均揭示,MEIS明显缺乏每个维度所设定的4因素的结构效度,项目效率明显不足,因此,MEIS尚不具备有效测量情绪智力的功能。     

中学生适应取向的心理健康结构初探

在文献综述的基础上,建构了适应取向的中学生心理健康的理论模型,并对中学生和中学教师进行开放式问卷调查,再参考同类量表,拟定了中学生心理健康量表的题项。经对1,567名中学生进行测试,结果表明:适应取向的中学生心理健康包含生活幸福、乐于学习、人际和谐、考试镇静、情绪稳定等五个维度,本研究所编制的中学生心理健康量表具有良好的信效度。     

自我韧性量表与Connor-Davidson韧性量表的应用比较

目的:考察自我韧性量表中文版的心理测量学指标,探讨其与Connor-Davidson韧性量表的关系,比较两者在中国人群中的应用效果。方法:在社区人群中施测自我韧性量表和Connor-Davidson韧性量表的中文版,以及自尊量表、生活满意度指数A问卷、大五人格问卷。结果:自我韧性量表中文版的内部一致性系数为0.77,略低于Connor-Davidson韧性量表。自我韧性量表与Connor-Davidson韧性量表的相关系数为0.61。在以自尊、生活满意度、大五人格为效标时,偏相关分析表明控制了Connor-Davidson韧性量表得分后,自我韧性量表与效标的相关未达到显著水平(除大五人格的外向性维度外);但控制了自我韧性量表得分后,Connor-Davidson量表与效标的相关仍达到显著水平(除开放性维度外)。结论:在我国人群的应用中,Connor-Davidson韧性量表优于自我韧性量表,是值得推广的韧性测量工具。     

A Bayesian predictive analysis of test scores

In the classical test theory, a high-reliability test always leads to a precise measurement. However, when it comes to the prediction of test scores, it is not necessarily so. Based on a Bayesian statistical approach, we predicted the distributions of test scores for a new subject, a new test, and a new subject taking a new test. Under some reasonable conditions, the predicted means, variances, and covariances of predicted scores were obtained and investigated. We found that high test reliability did not necessarily lead to small variances or covariances. For a new subject, higher test reliability led to larger predicted variances and covariances, because high test reliability enabled a more accurate prediction of test score variances. Regarding a new subject taking a new test, in this study, higher test reliability led to a large variance when the sample size was smaller than half the number of tests. The classical test theory is reanalyzed from the viewpoint of predictions and some suggestions are made.     

The proper sequence for correcting correlation coefficients for range restriction and unreliability

Corrections of correlations for range restriction (i.e., selection) and unreliability are common in psychometric work. The current rule of thumb for determining the order in which to apply these corrections looks to the nature of the reliability estimate (i.e., restricted or unrestricted). While intuitive, this rule of thumb is untenable when the correction includes the variable upon which selection is made, as is generally the case. Using classical test theory, we show that it is the nature of the range restriction, not the nature of the available reliability coefficient, that determines the sequence for applying corrections for range restriction and unreliability.We would like to thank Malcolm James Ree for his encouragement and helpful comments as well as those of the editors, associate editor, and reviewers.     

Effect size, power, and sample size determination for structured means modeling and mimic approaches to between-groups hypothesis testing of means on a single latent construct

While effect size estimates, post hoc power estimates, and a priori sample size determination are becoming a routine part of univariate analyses involving measured variables (e.g., ANOVA), such measures and methods have not been articulated for analyses involving latent means. The current article presents standardized effect size measures for latent mean differences inferred from both structured means modeling and MIMIC approaches to hypothesis testing about differences among means on a single latent construct. These measures are then related to post hoc power analysis, a priori sample size determination, and a relevant measure of construct reliability.I wish to convey my appreciation to the reviewers and Associate Editor, whose suggestions extended and strengthened the article's content immensely, and to Ralph Mueller of The George Washington University for enhancing the clarity of its presentation.     

青少年心理韧性量表（HKRA）的修订

心理韧性研究起源于20世纪70年代,而国内的相关研究还刚刚处于起步阶段,为有利于国内心理韧性研究的开展,选定青少年心理韧性量表(HKRA)进行中文版修订。以初中二年级学生884人(男生468人,女生416人)为被试,采用探索性因子分析法,共提取11个因子,其中外部保护因子7个,心理韧性特质因子4个,各个题目在相应因子上的载荷在0.34-0.88之间,各个因子的同质性信度在0.62-0.84之间,累积方差解释率为55.77%。结果表明,量表符合测量学的信度和效度要求,可以作为测量心理韧性的工具在国内使用。     

坚韧人格量表的编制

通过开放式问卷调查、专家访谈及参考国外同类问卷,结合中国社会文化特点,编制了坚韧人格量表。经过两次施测,对数据分别进行探索性因素分析及验证性因素分析,最终确定坚韧人格量表包含四个维度,共27个项目。数据分析表明,坚韧人格量表具有良好的信度和效度,可以作为人格坚韧性的测量工具。