Digital Module 16: Longitudinal Data Analysis

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.     

Digital Module 05: Diagnostic Measurement—The G‐DINA Framework https://ncme.elevate.commpartners.com

In this ITEMS module, we introduce the generalized deterministic inputs, noisy “and” gate (G‐DINA) model, which is a general framework for specifying, estimating, and evaluating a wide variety of cognitive diagnosis models. The module contains a nontechnical introduction to diagnostic measurement, an introductory overview of the G‐DINA model, as well as common special cases, and a review of model‐data fit evaluation practices within this framework. We use the flexible GDINA R package, which is available for free within the R environment and provides a user‐friendly graphical interface in addition to the code‐driven layer. The digital module also contains videos of worked examples, solutions to data activity questions, curated resources, a glossary, and quizzes with diagnostic feedback.     

The effect of number of siblings and birth order on educational attainment: Empirical Evidence from Chinese General Social Survey

Data from China demonstrate that the effect of the number of siblings on education is restricted by many factors, such as children’s gender, urban or rural household registration, whether there is only one child, the birth order of children within the family, and parents’ status. Chinese families have significant preferences for the eldest son and the youngest son. Moreover, research based on the natural experiment and instrumental variable approach suggests that market-oriented reform of education has increased the cost of family education expenditures since China’s reform and opening up, which further aggravates the negative impact on education of having many siblings in an urban setting.     

空间连杆机构装配构形的建模及求解

提出完全有效元素法并用于建立一类空间连杆机构装配构形问题的统一数学模型;将综合消元法用于确定机构的所有装配构形。实例计算表明,本文理论正确、方法实用新颖、程序运行可靠。     

国内运动生物力学发展现状思考

运动生物力学是一门新兴的边缘性科学，其定义、研究范畴、研究方法都有待商榷。从这三个角度出发，主要对大量资料进行归纳总结，综合、概括了目前国内运动生物力学发展状况。力求对我国的运动生物力学发展的状况勾勒出一个清晰的脉络图，以便在这门学科今后的研究中减少盲目性，具有更强的实用性。     

“中学体育教材”存在的问题与解决途径

中学部分体育教材存在教不了、教不完、教不明、教不深、教不好等问题 ,这些问题的出现是有原因的。解决的途径和方法应该是对体育课程全方位地再设计和改进 ,从整体上重新调整体育课程体系。     

影响三级跳远成绩的若干因素

通过阅读、整理国内外有关三级跳远方面的献资料，阐明三级跳远中助跑速度、起跳技术、三跳比例、力量以及平衡对三级跳远成绩的影响，为三级跳远的研究提供参考。     

Schwarz不等式及旋转体侧面积的计算问题

文章应用Schwarz不等式的知识,给出了旋转体侧面积计算公式的一个新颖的证明,并同时指出用定积分计算旋转体侧面积时应该避免发生的错误。     

新时期体育应践行"以人为本"理念

以人为本作为科学发展观的核心已成为新时期我国各项工作的行动指南。体育作为我国社会主义现代化建设事业的重要组成部分,在新的历史时期践行以人为本理念,已成为一个迫切需要解决的问题。在新的历史时期,体育领域践行以人为本理念有其丰富的理论源泉和现实依据。     

哪些研究问题需要用分层线性模型回答

采用常规的回归分析或方差分析处理行为科学与社会科学研究中经常遇到的嵌套数据，不能满足独立观察的假定，得到的标准误差较小，导致I型错误扩大化，同时，也不利于对不同层次变量不同作用的探讨，分层线性则明确区分数据层次，通过对个体水平变量和组别水平变量的分层综合分析，避免了上述弊病，因而可对个体水平的变量进行更准确的预测和更合理的解释，通过实例介绍了将研究问题与分层线性模型有机结合的方法。