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.     

物理模型与股票投资

股票投资的方法很多，建立物理模型进行投资是一种简明有效的方法，使用金字塔模型和平衡理论对股票进行操作，能把握最佳投资机会。     

<体育与健康课程标准>实施进程研究

经过反复的调查和对文献资料的分析，初步提出：体育与健康课程模式的多元化，是新“课标”由目标理念向操作化进程的有效途径。课程模式多元化，要以单元为基础，构建模块组合；以新“课标”为母体，构建子项模式；以新“课标”为依据，完善结构体系；以模式为中介，超越课程模式。     

帆板实际航行中运动学参数的测定

对帆板运动进行三维解析即可有效地分析运动员的操作技能，也可利用测定的运动学参数反过来计算与检验空气动力学参数与水动力学参数。介绍了帆板运动的运动学参数、测定的方法。分析了帆板运动学参数测试的可行性。     

园林景观动画设计初探

本文通过对计算机三维动画的相关理论与技术的初步探讨，并结合环境景观动画的制作实例，介绍了该技术在园林景观动画设计方面的应用和发展前景。     

邢傲伟跳马侧手翻直体侧空翻转体810°的运动学分析

通过运动学等研究方法,揭示了我国优秀运动员邢傲伟完成的跳马侧手翻直体侧空翻转体810°的运动学规律与技术特点,对于进一步发展笠松类高难动作,提高我国男女跳马技术水平有促进作用.     

杨亚红和王湉湉跳马前手翻直体前空翻转体540°的三维运动学分析

运用三维运动学法对中国体操女子集训队员--杨亚红和王湉湉的跳马前手翻直体前空翻转体540°的动作进行了对比性技术分析,并针对二人动作完成的情况进行了技术性诊断.以期对我国跳马前手翻直体前空翻转体540°动作的训练和技术改进提供参考依据.