Examining the Rule of Thumb of Not Using Multilevel Modeling: The “Design Effect Smaller Than Two” Rule     

Mark H. C. Lai  Oi-man Kwok 《Journal of Experimental Education》2015,83(3):423-438

Educational researchers commonly use the rule of thumb of “design effect smaller than 2” as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models (which differ in the location of the clustering effect). With a 3 (design effect) × 5 (cluster size) × 4 (number of clusters) Monte Carlo simulation study we found that the rule should not be applied when researchers: (a) are interested in the effects of higher-level predictors, or (b) have a cluster size less than 10. Implications of the findings and limitations of the study are discussed.  相似文献   

大学生图书馆借阅分析研究--以三明学院为例     

刘桂红  管强  林静洁 《乐山师范学院学报》2015,(6)

利用聚类分析法和主成分分析法对图书馆繁杂的借阅数据及流通数据进行分析,揭示大学生图书馆借阅三个主要特点：功利性借阅明显,专业型阅读目的显著,消遣性的阅读倾向突出。并根据这些特点为图书馆提出相关的建议。  相似文献   

Do labels matter? Analysis of teachers' self-efficacy towards the autism spectrum disorder depending on the diagnostic label used (ASD or Asperger's)     

Irene Gómez-Marí  Gemma Pastor-Cerezuela  Irene Lacruz-Pérez  Raúl Tárraga-Mínguez 《Journal of Research in Special Educational Needs》2023,23(2):126-135

Changes in the classification of autism and Asperger's syndrome led to changes in social perception of ASD. Since last criteria, studies indicate higher levels of stigma towards ASD than towards Asperger's. These prejudices are barriers to inclusive education. Thus, it is relevant (1) to evaluate pre-service teachers' self-efficacy towards the label of ASD; (2) to evaluate pre-service teachers' self-efficacy towards the label of Asperger's and (3) to compare those results to analyse whether the use of different diagnostic labels brings about different levels of self-efficacy. One hundred and eighty-six primary education pre-service teachers participated in the current study. Two adaptations of the Autism Self-Efficacy Scale for Teachers (ASSET) were used: a version with the label of ‘ASD’ (n = 96) and another for ‘Asperger's’ (n = 90). The scores obtained by the group asked about ASD were high according to the ASSET score range, while the scores obtained by the group asked about Asperger's were medium. After comparing the results, participants asked about the label ASD showed higher levels of self-efficacy than participants asked about Asperger's. These results could be a consequence of the consolidation of the ASD diagnosis among society and the higher presence of children with ASD in schools and cultural products, among other factors.  相似文献   

从SCI论文统计分析看瓜尔豆研究进展     

李文芯  张银铃  李宏建  刘渠华 《科技广场》2014,(8):112-116

根据Web ofScience收录论文的统计数据,分析了国际瓜尔豆研究的进展和学科领域的研究情况,根据瓜尔豆的研究成果在SCI收录论文上所反映发生的差异和变化,并以此为依据,对瓜尔豆领域的研究、应用和发展提出了意见。  相似文献   

基于灰色理论的工程造价咨询企业信用评价实证研究     

王雪青  陈伟唯  陈杨杨  韩涛涛 《科技管理研究》2014,(22)

以工程造价咨询企业为研究对象,构建其信用评价指标体系;针对其信用信息数据搜集难度大、指标数量多、相关性强的特点,以主成分分析法作为指标约简和赋权方法,以三角白化权函数灰色聚类作为信用分类方法构建其信用评价模型;最后以宁波市30个工程造价咨询企业为样本集进行实证分析,结果表明该评价模型能够较好地处理小样本、高维数的信用数据,同时具有准确率高、分类区分度好、误判成本低的优点。  相似文献   

基于国外博士学位论文的知识管理研究热点及趋势     

李干  袁勤俭 《现代情报》2014,34(6):41-47

以PQDT数据库中1984-2013年间共729篇国外知识管理领域博士学位论文为研究对象,采用Excel、SPSS软件进行共词分析、聚类分析和战略坐标图分析。结果显示：国外知识管理领域博士论文的研究主要集中在9个方面,其中知识形态研究、信息技术与知识管理系统研究、组织学习与战略管理研究是核心热点,企业创新与资本研究处于成熟研究区域,人工智能与决策支持研究处于研究的边缘位置,电子商务与知识整合研究、知识管理方式研究、知识管理应用研究有可能成为新的研究热点,组织文化研究具有发展为核心研究热点的潜力。  相似文献   

Contrastive and attentive graph learning for multi-view clustering     

《Information processing & management》2022,59(4):102967

Graph-based multi-view clustering aims to take advantage of multiple view graph information to provide clustering solutions. The consistency constraint of multiple views is the key of multi-view graph clustering. Most existing studies generate fusion graphs and constrain multi-view consistency by clustering loss. We argue that local pair-view consistency can achieve fine-modeling of consensus information in multiple views. Towards this end, we propose a novel Contrastive and Attentive Graph Learning framework for multi-view clustering (CAGL). Specifically, we design a contrastive fine-modeling in multi-view graph learning using maximizing the similarity of pair-view to guarantee the consistency of multiple views. Meanwhile, an Att-weighted refined fusion graph module based on attention networks to capture the capacity difference of different views dynamically and further facilitate the mutual reinforcement of single view and fusion view. Besides, our CAGL can learn a specialized representation for clustering via a self-training clustering module. Finally, we develop a joint optimization objective to balance every module and iteratively optimize the proposed CAGL in the framework of graph encoder–decoder. Experimental results on six benchmarks across different modalities and sizes demonstrate that our CAGL outperforms state-of-the-art baselines.  相似文献   

Demand forecasting model using hotel clustering findings for hospitality industry     

《Information processing & management》2022,59(1):102816

Tourism has become a growing industry day by day with the developing economic conditions and the increasing communication and social interaction ability of the people. Forecasting tourism demand is not only important for tourism operators to maximize their revenues but also important for the formation of economic plans of the countries on a global scale. Based on the predictions countries are able to regulate the sectors that benefit economically from tourism locally. Therefore, it is crucial to accurately predict the demand in many weeks advance. In this study, we propose a new demand forecasting model for the hospitality industry that forecasts weekly hotel demand four weeks in advance through Attention-Long Short Term Memory (Attention-LSTM). Unlike most of the existing methods, the proposed method utilizes the time series demand data together with additional features obtained from K-Means Clustering findings such as Top 10 Hotel Features or Hotel Embeddings obtained using Neural Networks (NN). While creating our model, the clustering part was influenced by the fact that travelers choose their accommodation according to certain criteria, and the hotels meeting similar criteria may have similar demands. Therefore, before the clustering part, we also applied methods that would enable us to represent the features of the hotels more properly and we observed that 10-D Embedded Hotel Data representation with NN Embeddings came to the fore. In order to observe the performance of the proposed hotel demand forecasting model we used a real-world dataset provided by a tourism agency in Turkey and the results show that the proposed model achieves less mean absolute error and mean absolute percentage error (at worst % 3 and at most % 29 improvements) compared to the currently used machine learning and deep learning models.  相似文献   

基于孙子情报分析理论的战略情报分析框架构建     

叶利军 《情报杂志》2022,(1)

[研究目的]战略情报分析主要是由情报专家人工分析为主,在信息系统方面的建设还比较薄弱,文章结合情报分析过程,提出基于孙子情报分析理论构建标签体系,作为信息系统设计实现的一种参考。[研究方法]通过孙子情报分析理论、标签的定义、战略情报分析过程描述了战略情报分析标签体系的构建及其作用,提出了以顶层标签作为切入点构建战略问题分析模型,以及战略情报分析计算模型。[研究结论]标签体系应用广泛,以孙子情报分析理论的“道、天、地、将、法”为基础构建战略情报分析标签体系,进行战略问题分析建模与计算,对战略情报分析研究和相关信息系统建设具有一定的指导意义。  相似文献   

我国区域公共图书馆文化服务效率评价及差异分析     

黄敏  吕娇 《情报探索》2022,(1):115-119

[目的/意义]旨在提高我国公共图书馆文化服务效率,为公共图书馆文化服务发展提供参考。[方法/过程]以我国31个省份公共图书馆为数据,运用DEA-BCC模型和K-means聚类分析我国各区域文化服务的效率及差异。[结果/结论]我国公共图书馆文化服务效率整体较低,呈非均衡性,存在不同程度投入冗余和产出不足,最后针对我国公共图书馆文化服务提出相应的改进建议。  相似文献