Measurement Invariance Testing with Many Groups: A Comparison of Five Approaches

With the increasing use of international survey data especially in cross-cultural and multinational studies, establishing measurement invariance (MI) across a large number of groups in a study is essential. Testing MI over many groups is methodologically challenging, however. We identified 5 methods for MI testing across many groups (multiple group confirmatory factor analysis, multilevel confirmatory factor analysis, multilevel factor mixture modeling, Bayesian approximate MI testing, and alignment optimization) and explicated the similarities and differences of these approaches in terms of their conceptual models and statistical procedures. A Monte Carlo study was conducted to investigate the efficacy of the 5 methods in detecting measurement noninvariance across many groups using various fit criteria. Generally, the 5 methods showed reasonable performance in identifying the level of invariance if an appropriate fit criterion was used (e.g., Bayesian information criteron with multilevel factor mixture modeling). Finally, general guidelines in selecting an appropriate method are provided.     

The effect of toxicity on COVID-19 news network formation in political subcommunities on Reddit: An affiliation network approach

Political polarization remains perhaps the “greatest barrier” to effective COVID-19 pandemic mitigation measures in the United States. Social media has been implicated in fueling this polarization. In this paper, we uncover the network of COVID-19 related news sources shared to 30 politically biased and 2 neutral subcommunities on Reddit. We find, using exponential random graph modeling, that news sources associated with highly toxic – “rude, disrespectful” – content are more likely to be shared across political subreddits. We also find homophily according to toxicity levels in the network of online news sources. Our findings suggest that news sources associated with high toxicity are rewarded with prominent positions in the resultant network. The toxicity in COVID-19 discussions may fuel political polarization by denigrating ideological opponents and politicizing responses to the COVID-19 pandemic, all to the detriment of mitigation measures. Public health practitioners should monitor toxicity in public online discussions to familiarize themselves with emerging political arguments that threaten adherence to public health crises management. We also recommend, based on our findings, that social media platforms algorithmically promote neutral and scientific news sources to reduce toxic discussion in subcommunities and encourage compliance with public health recommendations in the fight against COVID-19.     

A micro-perspective on students’ behavioral engagement in the context of teachers’ instructional support during seatwork: Sources of variability and the role of teacher adaptive support

Despite increased acknowledgement of the significance of situational factors to engagement, engagement is traditionally seen as a student characteristic. In this study, we investigated to what extent variation in observational measures of behavioral student engagement during seatwork is due to students versus teachers, teacher-student dyads, or situational (i.e., variation in time) effects. Additionally, we studied whether adaptive support during teacher-student interactions contributes to student engagement following that interaction. A cross-classified multilevel analysis of 324 video- and audio-recorded secondary school teacher-student interactions showed that situational factors and error were the strongest source of variability in student engagement. Other than expected, teacher-related and dyad-related variability were limited. Although behavioral engagement after teacher-student interaction was significantly higher than pre-interaction student engagement, higher post-interaction levels were not related to the level of adaptive support provided during the teacher-student interaction. These findings imply that situational factors deserve more attention in engagement research, for example by investigating what situational factors contribute to engagement. For teachers, the time-variant, situation-dependent nature of engagement opens up valuable opportunities to actively design optimal learning situations.     

From Archive,to Access,to Experience––Historical Documents as a Basis for Immersive Experiences

Libraries have been the key to preserving culture and historic legacy for centuries. One such treasure cataloged in The Pennsylvania State University (Penn State) Libraries is a collection of over 33,000 Sanborn? Fire Insurance Maps. Originally kept safe in metal drawers, the library has embarked on a journey to digitize this abundance of information, combine it with other media such as photographs, and make it accessible through a web interface. Inspired by these efforts, we accessed this information and took it to the next level. Using state of the art 3D modeling and immersive technologies, we created a historic 3D model and immersive experiences of Penn State, exemplarily for the 1922 campus. The resulting experiences can be accessed through the web but also through head mounted displays (HMDs) and mobile phones in combination with VR viewers such as the Google Cardboard. Additionally, they can be used anywhere in the world or on the campus itself as a way to enable remote and in situ experiences and learning. Immersive experiences let us connect to the past, the present and the future, and as such offer value to digital cultural heritage efforts.     

基于改进的LOD模型算法三维场景建模

图形渲染速度目前已成为复杂场景漫游的主要瓶颈,为满足漫游系统的实时性需求,在详细分析传统LOD模型算法的基础上,提出了模型差值信息渐增的改进思想,解决了传统LOD模型算法中存在的重复渲染和多次建模的问题,减少了数据冗余,进一步提高了虚拟场景的漫游速度。     

基于Geomagic Design X的洗车水枪逆向建模

以洗车水枪为例,详细阐述了逆向建模的流程,并利用逆向工程软件GeomagicStudio软件和Geomagic Design X软件对扫描数据进行处理,得到了高质量的三维模型。该方法即可获得高质量的三维模型,还可缩短产品开发周期,具有较好的应用价值。     

数学建模思想在高职数学教学中的应用

加强培养学生的数学建模能力具有十分重要的意义.在高职数学教学中溶入数学建模思想,有利于提高学生的学习兴趣,提高教学效果,促进教学方式的创新.数学建模思想在高职数学教学中的应用:用“数学的抽象性”特征,启发学生对数学公式、定义的理解与认识;用“数学的普遍性”特征,启发学生思考所遇到的实际问题;运用高等数学中的“变换观点”,培养学生联想能力.     

A Second-Order Longitudinal Model for Binary Outcomes: Item Response Theory Versus Structural Equation Modeling

Measuring academic growth, or change in aptitude, relies on longitudinal data collected across multiple measurements. The National Educational Longitudinal Study (NELS:88) is among the earliest, large-scale, educational surveys tracking students’ performance on cognitive batteries over 3 years. Notable features of the NELS:88 data set, and of almost all repeated measures educational assessments, are (a) the outcome variables are binary or at least categorical in nature; and (b) a set of different items is given at each measurement occasion with a few anchor items to fix the measurement scale. This study focuses on the challenges related to specifying and fitting a second-order longitudinal model for binary outcomes, within both the item response theory and structural equation modeling frameworks. The distinctions between and commonalities shared between these two frameworks are discussed. A real data analysis using the NELS:88 data set is presented for illustration purposes.     

VDR,RXR, Coronin-1 and Interferonγ Levels in PBMCs of Type-2 Diabetes Patients: Molecular Link between Diabetes and Tuberculosis

Diabetes and tuberculosis are world’s most deadly epidemics. People suffering from diabetes are susceptible to tuberculosis. Molecular link between the two is largely unknown. It is known that Vitamin A receptor (RXR) heterodimerizes with Vitamin D receptor (VDR) and Peroxisome proliferator-activator receptor-γ (PPARγ) to regulate Tryptophan-aspartate containing coat protein (TACO) expression and fatty acid metabolism respectively, so it would be interesting to check the expression of these genes in diabetes mellitus (DM) patients which might explain the susceptibility of diabetics to tuberculosis. In this study, we checked the expression of RXR, VDR, TACO and Interferon-γ (IFNγ) genes in type-2 DM patients for understanding the link between the two diseases. We observed down regulation of RXR gene and corresponding up regulation of TACO gene expression. We have not observed significant change in expression of VDR and IFNγ genes in type-2 DM patients. Repression of RXR gene could hamper VDR-RXR heterodimer formation and thus would up regulate TACO gene expression which may predispose the type-2 DM patients to tuberculosis. Also, decrease in RXR-PPARγ heterodimer could be involved in DM.     

二元一次方程组在实际问题中的应用

本文以实际案例为依托,着重从解题思路和解题过程中折射出运用二元一次方程组解决实际问题的五大步骤。通过这种定型化思维的培养,使学生养成用数学建模思想和方程思想来解决生活中的实际问题的思维过程,这也是本文的价值和目的所在。