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针对患有自闭症谱系障碍幼儿的广泛性发育障碍评定量表的探索性和验证性因素分析。

Exploratory and confirmatory factor analyses of the pervasive developmental disorders rating scale for young children with autistic disorder.

作者信息

Eaves Ronald C, Williams Thomas O

机构信息

Department of Rehabilitation and Special Education, Auburn University, AL 36849, USA.

出版信息

J Genet Psychol. 2006 Mar;167(1):65-92. doi: 10.3200/GNTP.167.1.65-92.

Abstract

In this study, the authors examined the construct validity of the Pervasive Developmental Disorder Rating Scale (PDDRS; R. C. Eaves, 1993), which is a screening instrument used to identify individuals with autistic disorder and other pervasive developmental disorders. The PDDRS is purported to measure 3 factors--arousal, affect, and cognition-that collectively make up the construct of autism. Using scores from 199 children (aged 1-6 years) diagnosed with autistic disorder, the authors submitted data to exploratory and confirmatory factor analyses. In the 1st series of analyses, the authors analyzed a user-specified 3-factor solution using principal axis factor analysis with a promax rotation to evaluate the assertion of a correlated 3-factor structure. Next, the authors analyzed 1-factor and 2-factor solutions to determine if they provided a better factor structure for the data. In the 2nd series, the authors conducted confirmatory factor analyses, which compared the theorized hierarchical 2nd-order factor model with 5 plausible competing models. The results of the exploratory analyses supported the 3-factor solution. With the confirmatory analyses, the 2nd-order factor model provided the best fit for the data. The exploratory and confirmatory analyses supported the theoretical assumptions undergirding the development of the PDDRS. The authors discuss theoretical implications, practical implications, and areas for further research.

摘要

在本研究中,作者检验了广泛性发育障碍评定量表(PDDRS;R.C.伊夫斯,1993年)的结构效度,该量表是一种用于识别自闭症谱系障碍及其他广泛性发育障碍患者的筛查工具。PDDRS据称可测量三个因素——觉醒、情感和认知,这些因素共同构成了自闭症的结构。作者使用199名被诊断为自闭症谱系障碍的1至6岁儿童的得分,将数据提交进行探索性和验证性因素分析。在第一系列分析中,作者使用主轴因素分析和斜交旋转分析了用户指定的三因素解决方案,以评估相关三因素结构的主张。接下来,作者分析了单因素和双因素解决方案,以确定它们是否为数据提供了更好的因素结构。在第二系列分析中,作者进行了验证性因素分析,将理论上的二阶因素模型与5个合理的竞争模型进行了比较。探索性分析的结果支持了三因素解决方案。通过验证性分析,二阶因素模型对数据的拟合效果最佳。探索性和验证性分析支持了PDDRS编制所依据的理论假设。作者讨论了理论意义、实际意义以及进一步研究的领域。

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