多级纵向反应数据的成对建模

Pairwise modeling method for the polytomous longitudinal response data

项目反应理论(Item Responds Theory,简记为IRT)是教育测量与心理测量非常活跃的研究领域.纵向项目反应数据,主要是用来研究随着时间不断推移,被试者能力发生怎样变化的问题.针对分析过程中,当维数达到一定值时,计算机可能无法再运算出对应多重积分的值和运算的最终结果问题,采用成对建模方法来研究分析拓广分部评分模型(GPCM)下的纵向反应数据,有效地解决了多重积分复杂的计算问题,用模拟展现了成对建模方法的优势,进一步研究了相邻测验间的锚题数,即相同项目数对估计稳定性产生的影响,为更加合理的测验项目布局提供了有效的依据.

： Item Response Theory （IRT） is a very active area of research in the education and psychological measurement,Longitudinal item response data can be used to investigate the changes of latent traits for a group of subjects over time, in the research, when the dimension reaches a certain value,the Computer can not be able to calculate the results of multiple integrals. In this paper,pairwise modeling approach is applied to study the longitudinal item response data in Generalized Partial Credit Model（GPCM） ,showing the superiority of the pairwise modeling approach. Finally, the impact of the same items number between two consecutive instants on the stability of the estimates was studied, which would provide a valid basis for the mor reasonable project layout used to test.