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作 者:梁康俊 易少军 王琴 蔡艳[2] LIANG Kangjun;YI Shaojun;WANG Qin;CAI Yan(School of Information Engineering,Zhongshan Polytechnic,Zhongshan Guangdong 528404,China;School of Psychology,Jiangxi Normal University,Nanchang Jiangxi 330022,China;Department of Information Engineering,Gongqing College of Nanchang University,Gongqing Jiangxi 332020,China)
机构地区:[1]中山职业技术学院信息工程学院,广东中山528404 [2]江西师范大学心理学院,江西南昌330022 [3]南昌大学共青学院信息工程系,江西共青城332020
出 处:《江西师范大学学报(自然科学版)》2024年第6期622-631,共10页Journal of Jiangxi Normal University(Natural Science Edition)
基 金:国家自然科学基金(62467002,62167004)资助项目.
摘 要:在人格特质测量中,被试可能会做出符合社会期望回答的反应偏差(即社会称许反应偏差),这种反应偏差会严重威胁到测验的可靠性和有效性.为了有效地解决这个问题,该文基于2阶段序列加工过程(即检索信息过程和编辑过程),开发了一种考虑社会称许性的项目反应模型,以应对在人格测量中的社会称许效应.采用蒙特卡罗(Monte Carlo)模拟研究与实证研究相结合的研究范式,探讨了新开发模型的性能及其优势.研究结果表明:1)新开发的模型能有效地处理在人格测量中的社会称许效应;2)与传统的IRT模型相比,新模型能更好地拟合真实数据,且对被试特质参数估计精度更高.In personality trait measurement,respondents may exhibit response biases that align with social desirability(i.e.,socially desirable responding biases),which severely threatens the reliability and validity of assessments.To address this issue effectively,the novel item response theory(IRT)model incorporating social desirability is developed,grounded in the two-stage sequential processing framework(i.e.,information retrieval and editing processes),so as to mitigate social desirability effects in personality measurement.The hybrid research paradigm combining Monte Carlo simulation studies and empirical investigations are employed to evaluate the performance and advantages of the newly proposed model.The results show that the developed model effectively addresses social desirability effects in personality measurement.Compared to traditional IRT models,the new model exhibits superior fit to real data and provides higher accuracy in estimating respondents′trait parameters.
分 类 号:B841[哲学宗教—基础心理学]
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