Detecting Measurement Disturbances in Rater‐Mediated Assessments

The term measurement disturbance has been used to describe systematic conditions that affect a measurement process, resulting in a compromised interpretation of person or item estimates. Measurement disturbances have been discussed in relation to systematic response patterns associated with items and persons, such as start‐up, plodding, boredom, or fatigue. An understanding of the different types of measurement disturbances can lead to a more complete understanding of persons or items in terms of the construct being measured. Although measurement disturbances have been explored in several contexts, they have not been explicitly considered in the context of performance assessments. The purpose of this study is to illustrate the use of graphical methods to explore measurement disturbances related to raters within the context of a writing assessment. Graphical displays that illustrate the alignment between expected and empirical rater response functions are considered as they relate to indicators of rating quality based on the Rasch model. Results suggest that graphical displays can be used to identify measurement disturbances for raters related to specific ranges of student achievement that suggest potential rater bias. Further, results highlight the added diagnostic value of graphical displays for detecting measurement disturbances that are not captured using Rasch model–data fit statistics.     

Digital Module 06: Bayesian Psychometrics—Posterior Predictive Model Checking https://ncme.elevate.commpartners.com

Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model‐data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model‐data fit models is critical. In this instructional module, Allison Ames and Aaron Myers provide an overview of Posterior Predictive Model Checking (PPMC), the most common Bayesian model‐data fit approach. Specifically, they review the conceptual foundation of Bayesian inference as well as PPMC and walk through the computational steps of PPMC using real‐life data examples from simple linear regression and item response theory analysis. They provide guidance for how to interpret PPMC results and discuss how to implement PPMC for other model(s) and data. The digital module contains sample data, SAS code, diagnostic quiz questions, data‐based activities, curated resources, and a glossary.     

Digital Module 04: Diagnostic Measurement: Modeling Checklists for Practitioners https://ncme.elevate.commpartners.com

In this ITEMS module, we provide a didactic overview of the specification, estimation, evaluation, and interpretation steps for diagnostic measurement/classification models (DCMs), which are a promising psychometric modeling approach. These models can provide detailed skill‐ or attribute‐specific feedback to respondents along multiple latent dimensions and hold theoretical and practical appeal for a variety of fields. We use a current unified modeling framework—the log‐linear cognitive diagnosis model (LCDM)—as well as a series of quality‐control checklists for data analysts and scientific users to review the foundational concepts, practical steps, and interpretational principles for these models. We demonstrate how the models and checklists can be applied in real‐life data‐analysis contexts. A library of macros and supporting files for Excel, SAS, and Mplus are provided along with video tutorials for key practices.     

An NCME Instructional Module on Item‐Fit Statistics for Item Response Theory Models

Drawing valid inferences from item response theory (IRT) models is contingent upon a good fit of the data to the model. Violations of model‐data fit have numerous consequences, limiting the usefulness and applicability of the model. This instructional module provides an overview of methods used for evaluating the fit of IRT models. Upon completing this module, the reader will have an understanding of traditional and Bayesian approaches for evaluating model‐data fit of IRT models, the relative advantages of each approach, and the software available to implement each method.     

网站质量,用户感知及技术采纳行为的实证研究

本文以个体消费者为研究对象,从电子商务网站质量出发,结合用户的感知因素,在理论分析框架的基础上,构建了面向电子商务网站的技术采纳行为模型并提出了相应的研究假设.通过调查问卷收集样本,利用spss 软件对问卷进行了信度效度分析,采用结构方程模型软件Lisrel 对研究假设进行了检验.实证结果显示,网站质量的三个维度是影响用户的感知有用性和感知易用性的重要因素;感知娱乐对态度的影响是显著的;信任对态度和行为意向存在直接影响,而感知风险通过信任对态度和行为意向存在间接影响.     

供应商选择战略与制造战略一致性研究

选择合适、有能力的供应商成为制造企业提高绩效水平、获得竞争优势的重要保障.本文以23个国家的709个制造企业为研究对象,利用因子分析和层次回归分析揭示供应商选择战略与制造战略一致性的表现形式,以及一致性对运营绩效的影响.实证结果显示,供应商选择战略与制造战略之间呈现多纬一致性关系;6组一致性中,供应商发展能力与制造企业增值目标一致性与运营绩效呈现显著的正相关.本研究为制造企业选择供应商提供了理论和实践指导,也是战略一致性实证研究的一个有益补充.     

Fifteen To One

This article shows how data from a television game show can be used as a basis for illustrating many statistical procedures.     

中国西部中小城市社会体育现状与发展对策--以川南三市社会体育现状调查为例

以中国西部中小城市宜宾、泸州、乐山三市社会体育为切入点，具体分析三市市民参加体育活动的意识、基本情况以及影响体育锻炼的主要因素。提出了促进西部地区社会体育和体育经济全面发展的基本思路和改革举措。     

健身运动延缓免疫系统衰老机制的研究进展(综述)

人体的免疫系统随着年龄的增长发生生理性的衰退变化，从而导致机体免疫功能下降，感染疾病的几率增加。健身运动有望增强机体免疫机能，达到延缓衰老的目的。     

徐州市城区晨练老年人健身现状研究

通过问卷调查法、专家访谈法等方法对徐州市城区晨练老年人晨练健身消费现状进行调查,结果显示:徐州市城区晨练老年人的经济来源主要是靠自己的离退休金,并且每年在健身方面的消费总体水平较低;消费动机是为了满足健身的需要,多数人认同“花钱买健康”。