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在探索性结构方程建模框架下对文字效应建模的系统评估.

Luis Eduardo Garrido1, Alexander P Christensen2, Hudson Golino3

  • 1School of Psychology, Pontificia Universidad Catolica Madre y Maestra, Santo Domingo, Dominican Republic.

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概括

调查中的措辞影响可能会扭曲结果. 随机拦截项目因子分析 (RIIFA) 与其他方法不同,有效地减轻了探索性结构方程模型 (ESEM) 中的这些偏差.

关键词:
这就是ESEM的意义.项目的措辞 项目的措辞方法因子方法因子负面的措辞 负面的措辞响应偏差是指响应偏差.

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科学领域:

  • 心理测量 心理测量 心理测量
  • 行为科学 行为科学
  • 卫生健康科学科学 医学

背景情况:

  • 措辞效应,从不一致的反应到正面和负面措辞的项目中的系统变异,在行为和健康研究中很常见.
  • 解决措辞效应的现有方法在探索性结构方程模型 (ESEM) 中的评估有限.

研究的目的:

  • 评估不同响应偏差建模策略与ESEM中的措辞效应的性能.
  • 为了比较相关的特征相关方法减去一个 (CTC[M-1]) 模型,随机拦截项目因子分析 (RIIFA) 和无校正方法的有效性.

主要方法:

  • 蒙特卡洛模拟用于操纵响应偏差类型和大小,因子负载,因子相关性和样本大小.
  • 该研究检查了这些操纵对ESEM模型的影响,使用CTC[M-1],RIIFA和基线方法.

主要成果:

  • 忽视文本效应会显著降低ESEM模型的合适性,并扭曲估计.
  • 在减轻偏差和恢复准确的因子结构方面,RIIFA表现出卓越的表现.
  • 在CTC[M-1]模型中,当偏见对正面和负面措辞的项目产生影响时,其存在局限性.

结论:

  • 词效应需要在ESEM中小心处理,以确保有效的结果.
  • 推RIIFA用于解决ESEM中的措辞效应,提供了一个强大的解决方案.
  • 研究人员应谨慎对待方法因子解释,因为它们可以吸收实质差异.