The biasing effects of selection and attrition on estimating the mean

Organizational and validation researchers often work with data that has been subjected to selection on the predictor and attrition on the criterion. These researchers often use the data observed under these conditions to estimate either the predictor or criterion's restricted population means. We show that the restricted means due to direct or indirect selection are a function of the population means plus the selection ratios. Thus, any difference between selected mean groups reflects the population difference plus the selection ratio difference. When there is also attrition on the criterion, the estimation of group differences becomes even more complicated. The effect of selection and attrition induces measurement bias when estimating the restricted population mean of either the predictor or criterion. A sample mean observed under selection and attrition does not estimate either the population mean or the restricted population mean. We propose several procedures under normality that yield unbiased estimates of the mean. The procedures focus on correcting the effects of selection and attrition. Each procedure was evaluated with a Monte Carlo simulation to ascertain its strengths and weaknesses. Given appropriate sample size and conditions, we show that these procedures yield unbiased estimators of the restricted and unrestricted population means for both predictor and criterion. We also show how our findings have implications for replicating selected group differences.     

可修改答案的计算机化自适应测验的方法

与传统的纸笔测验(Paper And Pencil Based Test, P&P)相比计算机化自适应测验(Computerized Adaptive Testing, CAT)根据被试的作答反应自适应地选择题目, 它不仅缩短了测验长度, 还极大地提高了测验的准确性。然而, 目前绝大多数CAT不允许被试修改答案, 研究者主要担心修改答案会降低CAT的有效性。允许修改答案符合被试一贯的测验习惯, 修改之后的分数更能反映被试真实的水平, 从而能够进一步促进CAT在实际中的应用。现有的研究主要从三个方面提出了可修改答案CAT的控制方法：一是测验设计; 二是改进选题策略; 三是建构模型。未来的研究应进一步探讨这些方法之间的比较与结合, 以及对可修改答案认知诊断CAT (Cognitive Diagnostic CAT, CD-CAT)的研究。     

怀旧的触发、研究范式及测量

怀旧指的是个体怀念过去的事物、人物、地方甚至经历或感受。它大多与美好的记忆联系在一起, 并会带来积极的情绪体验, 但同时可能也会引起消极的情绪体验。怀旧对维持个体身心健康有一定的积极效用。本文着重介绍了怀旧的触发因素包括客观刺激的视觉、嗅觉、听觉及主观刺激的消极情绪与低温知觉, 分析了其研究范式有质化研究(内容分析与扎根理论)、量化研究(问卷调查与经验取样法)和实验研究(单因素随机实验设计与多因素实验设计), 并介绍了其相关的测量工具。未来研究要加强主动怀旧与被动怀旧、积极怀旧与消极怀旧的探讨; 整合各种研究范式与强化纵向的追踪研究; 以及要区分特质型怀旧与状态型怀旧。     

认知诊断CAT中具有非统计约束选题方法的比较

项目曝光控制和内容约束关系到测验安全、测验的信度和效度, 是计算机化自适应测验(Computerized Adaptive Testing, CAT)中两类重要的非统计约束条件。本文在认知诊断CAT中针对内容约束和项目曝光控制要求, 运用5种方法选择测验项目。它们分别是：(1) Monte Carlo方法与项目合格方法相结合, 记为MC-IE; (2) Monte Carlo方法与最大优先指标方法相结合, 记为MC-MPI; (3) Monte Carlo方法与限制阈值方法相结合, 记为MC-RT; (4) Monte Carlo方法与限制进度指标方法相结合, 记为MC-RPG以及(5) Monte Carlo方法与最大后验概率方法相结合, 记为MC-PP。然后通过在线性、收敛、发散、无结构和独立五种属性结构下构建题库并运用重参化融融统和模型模拟被试反应比较它们的选题表现。研究发现, (1) 相同选题方法在不同属性结构下项目曝光率的分布类似, 测量精度按线性、收敛、发散、无结构和独立结构的顺序依次降低; (2) 相同属性结构下, 不同方法的测量精度高低依次为MC-PP、MC-IE、MC-RT、MC-MPI和MC-RPG方法; 项目曝光均匀性优劣依次为MC-RPG、MC-MPI、MC-RT、MC-IE和MC-PP方法。统一量纲值表明, MC-RPG方法的综合表现最好, MC-MPI方法的表现次之。     

音乐诱发情绪测量及其影响因素*

使用音乐诱发情绪是有效且特殊的诱发方式。本文对音乐诱发情绪的自我报告测量、心理生理测量和功能神经成像测量进行了系统的梳理,并阐述了一种基于音乐特定模型的情绪测量方法。文章从音乐刺激的选择、听者特征以及情境特征三方面对影响音乐情绪测量的因素进行了总结。并为保证测量的准确性进一步提出确定理论模型一致性、结合多元方法、利用有效刺激材料、认真考评情境和参与者特征等解决思路,并阐明了此领域的研究趋势。     

‘Additive difference’ models without additivity and subtractivity

This paper studies conjoint measurement models tolerating intransitivities that closely resemble Tversky's additive difference model while replacing additivity and subtractivity by mere decomposability requirements. We offer a complete axiomatic characterisation of these models without having recourse to unnecessary structural assumptions on the set of objects. This shows the pure consequences of several cancellation conditions that have often been used in the analysis of more traditional conjoint measurement models. Our models contain as particular cases many aggregation rules that have been proposed in the literature.     

Empirical Guidance for Time-Window Sequential Analysis of Single Cases

Time-window sequential analyses test whether a target behavior occurs within a temporal window (e.g., within 2 seconds) after an antecedent behavior more than is expected by chance. This type of question is common when we need to know how one person or event may immediately affect another event or person in the natural environment. Theoretically, the significance of sequential associations from time-window analysis can be tested on the single subject level (Bakeman & Quera, 1995). The present Monte Carlo study was conducted to test the Type I error rates and the difference in sequential associations derived from four methods of time-window sequential analysis. The four methods vary according to whether they analyze the duration of antecedent and target behaviors. The results indicate that time-window sequential analysis method is generally valid. The results were most accurate when antecedent duration and target onset was analyzed. Although analyzing duration of the antecedent did affect the results, the effect size for the difference in results due to presence or absence of measuring duration of the antecedent was extremely small. Time-window analysis results appear unaffected by the decision to analyze the duration of the target event.     

Curriculum-based measures of writing across grade levels

This study compared the technical adequacy of curriculum-based measures in written expression across diverse grade levels. Students (n = 484) completed two narrative writing samples in response to story starters. Samples were scored for the number of words written (TW), the number of correct word sequences (CWS), and the number of correct minus incorrect word sequences (CWS-ICWS). Alternate-form reliability and criterion-related validity coefficients of the curriculum-based measures were examined to determine differences between the coefficients according to grade level.Results indicated moderate to strong alternate-form reliability coefficients and variable criterion-related validity coefficients. The data from this study support the need for curriculum-based measures of writing to become more complex as students age and become more skilled.     

基于人工神经网络的一种效度凭证求取方法

针对基于统计学的效度凭证求取方法所存在的问题,提出了基于人工神经网络的效度凭证求取方法。蒙特卡罗模拟实验和对实际数据的分析表明,当测验分数和效标分数为单变量且非线性关系时,或者测验分数和效标分数为多变量时,运用神经网络方法可以比统计学方法更好地求取心理测验效度的基于和其他变量关系的凭证。