Optimal design for online generated intelligence tests

在线生成智力测试的优化设计

• 批准号: 52261310
• 负责人: Professor Dr. Heinz Holling
• 金额: --
• 依托单位: Institut für Mathematische Stochastik (IMST)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2007
• 资助国家: 德国
• 起止时间: 2006-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/52261310?language=en
• 关键词: Optimal; design; online; generated; intelligence

In the first and second phase of this project rule-based items measuring reasoning and mental speed have been developed. These items which are generated on the fly have been calibrated using linear logistic test models and Rasch Poisson counts models. To efficiently estimate the parameters optimal designs for both models including fixed as well as random effects have been derived. Furthermore, an extensible test platform based on R is provided as open source software.The developments of the first and second phase are to be continued in the third phase. First, rule-based items to measure memory capacity will be created and integrated in the test platform. Thus, all components of the Berlin intelligence structure model besides divergent thinking can be measured using rule-based items on the fly. Second, the construct validity of rule-based items measuring reasoning will be analysed when these items are applied at several times. Further dependent variables to be studied are the within-family variance of the items parameters, the invariance of these parameters and the growth curve of the performance.

在该项目的第一和第二阶段，已经开发了基于规则的项目，用于测量推理和心理速度。使用线性逻辑检验模型和Rasch Poisson计数模型对这些动态生成的项目进行了校准。为了有效地估计参数的最优设计的两个模型，包括固定以及随机效应已经推导出来。此外，还提供了一个基于R语言的可扩展测试平台，作为开源软件。第一阶段和第二阶段的开发将在第三阶段继续进行。 首先，将创建基于规则的项目来测量记忆容量，并将其集成到测试平台中。 因此，柏林智力结构模型的所有组成部分，除了发散性思维，都可以使用基于规则的项目进行测量。其次，分析了规则推理测验项目在多次应用时的结构效度。进一步研究的因变量是项目参数的家庭内方差，这些参数的不变性和性能的增长曲线。

项目成果

Optimality regions for designs in multiple linear regression models with correlated random coefficients

具有相关随机系数的多元线性回归模型设计的最优区域

• DOI: 10.1016/j.jspi.2020.04.004
• 发表时间: 2020
• 期刊: arXiv: Statistics Theory
• 作者: Graßhoff;Holling;Röttger;Schwabe
• 通讯作者: Schwabe

Optimal designs for K-factor two-level models with first-order interactions on a symmetrically restricted design region

对称限制设计区域上具有一阶相互作用的 K 因子两级模型的优化设计

• DOI: 10.1007/s00362-018-01063-x
• 发表时间: 2019
• 期刊: Statistical Papers
• 影响因子: 1.3
• 作者: Freise;Schwabe
• 通讯作者: Schwabe

Optimal Design for the Rasch Poisson-Gamma Model

Rasch Poisson-Gamma 模型的优化设计

• DOI: 10.1007/978-3-319-31266-8_16
• 发表时间: 2016
• 作者: Graßhoff;Holling;Schwabe
• 通讯作者: Schwabe

Optimal designs for two-level main effects models on a restricted design region

受限设计区域上两水平主效应模型的优化设计

• DOI: 10.1016/j.jspi.2019.04.005
• 发表时间: 2020
• 期刊: Journal of Statistical Planning and Inference
• 影响因子: 0.9
• 作者: Freise;Holling;Schwabe
• 通讯作者: Schwabe

Retest effects in cognitive ability tests: A meta-analysis

• DOI: 10.1016/j.intell.2018.01.003
• 发表时间: 2018-03-01
• 期刊: INTELLIGENCE
• 影响因子: 3
• 作者: Scharfen, Jana;Peters, Judith Marie;Holling, Heinz
• 通讯作者: Holling, Heinz