多特征-多方法矩阵在50!

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2009-07-23 DOI:10.1027/1614-2241.5.3.71
M. Eid, Fridtjof W. Nussbeck
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引用次数: 36

摘要

50年前,也就是1959年,坎贝尔和菲斯克发表了心理学领域最具影响力的论文之一。在他们的文章《多特征多方法矩阵的收敛和判别验证》中,他们认为,为了测试验证的目的,考虑一个构造的一个单一操作化是不够的,而是需要多个构造的多个测量。坎贝尔和菲斯克建议至少使用两种不同的方法来测量构造。此外,坎贝尔和菲斯克明确指出,不可能得到一种不受特定方法影响的特征测量方法。在科学中,无论何时,我们测量一个结构(一个特征),我们都必须使用特定的测量方法。因此,性状和方法同时影响观察得分。为了将方法与特定性状的影响分离开来,因此在验证过程中总是需要考虑多个性状和多个方法。Campbell和Fiske提出了多特征多方法(multitraitmultimethod, MTMM)矩阵来分析收敛效度和判别效度。MTMM矩阵由代表不同方法测量的不同特征的所有多个度量之间的相关性组成。这些相关性可以通过坎贝尔和菲斯克制定的几个标准来评估。如果同一构念的不同测量是高度相关的,这证明了收敛效度。如果一个构念的不同测量与另一个构念的测量不相关,这表明区别效度。Campbell和Fiske的文章对心理学产生了巨大的影响(Eid & Diener, 2006)。这是《心理学公报》(Psychological Bulletin)上发表的被引用次数最多的论文(Sternberg, 1992)。迄今为止,该论文已被引4735次(Social Science Citation Index, February 27, 2009, 3:41 pm),且被引率呈上升趋势。他们的文章不仅对测试验证研究有重要影响,而且对方法学研究也有很大影响,因为许多研究人员已经开发了分析MTMM数据的新方法,并试图克服与分析MTMM矩阵的先前方法相关的一些问题和局限性。本期特刊致力于表彰坎贝尔和菲斯克的有影响力的工作。它提出了分析MTMM数据的三种不同的现代方法。所有贡献者都使用相同的数据集来说明他们的方法。这使读者能够集中精力比较不同的方法,分析收敛效度和判别效度的方式,以及如何识别和量化特征和方法特定的影响。数据包括三种人格特征(外向性、神经质和尽责性),由三名评价者(一名自我评价者和两名同伴评价者)评估。每个量表由四个项目组成(形容词,如健谈、认真等),按五分制进行评分。样本量n = 481。Maas, Lensvelt-Mulders和Hox在他们的多层多特征多方法分析中展示了多层模型如何应用于分析MTMM数据。Oort提出了对多特征多方法数据的三模式模型的应用,Nussbeck、Eid、Geiser、Courvoisier和Lischetzke展示了如何用CTC(M-1)模型对不同类型的评分者进行数据分析。最后,Hofling、Schermelleh-Engel和Mossbrugger比较了这些方法对分析多特征多方法(MTMM)数据的贡献:三种方法的比较。我们希望读者能乐于看到这一重要的方法论研究领域在过去几年中是如何发展的。
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The Multitrait-Multimethod Matrix at 50!
Fifty years ago, in 1959, Campbell and Fiske published one of the most influential papers in psychology. In their article Convergent and discriminant validation by the multitraitmultimethod matrix, they argued that it is not sufficient to consider one single operationalization of one construct for purposes of test validation but that multiple measures of multiple constructs are necessary. Campbell and Fiske recommended using at least two methods that are as different as possible for measuring the constructs. Moreover, Campbell and Fiske made clear that it is not possible to get a measure of a trait that is free of method-specific influences. Whenever, in science, we measure a construct (a trait) we have to use a specific measurement method. Therefore, it is the trait and the method that influence the observed score simultaneously. In order to separate methodfrom traitspecific influences, it is thus always necessary to consider more than one trait and more than one method in the validation process. Campbell and Fiske proposed the multitraitmultimethod (MTMM) matrix for analyzing the convergent and discriminant validity. The MTMM matrix consists of the correlations between all multiple measures representing the different traits measured by the different methods. These correlations can be evaluated by several criteria that have been developed by Campbell and Fiske. If the different measures of the same construct are highly correlated, this proves convergent validity. If the different measures of one construct are not correlated with the measures of another construct, this indicates discriminant validity. Campbell and Fiske’s article had and has an enormous influence on psychology (Eid & Diener, 2006). It is the most often cited paper that has ever been published in Psychological Bulletin (Sternberg, 1992). To date, it has been cited 4,735 times (Social Science Citation Index, February 27, 2009, 3:41 pm), and its citation rate is increasing. Their article does not only have an important impact on test validation studies but also has a strong impact on methodological research as many researchers have developed new approaches for analyzing MTMM data and tried to overcome some of the problems and limitations that are related to former approaches of analyzing MTMM matrices. This special issue is dedicated to honoring Campbell and Fiske’s influential work. It presents three different modern approaches for analyzing MTMM data. All contributors use the same data set illustrating their approaches. This enables readers to concentrate on the comparison of the different approaches with respect to the way convergent and discriminant validity can be analyzed as well as how traitand method-specific influences can be identified and quantified. The data consists of three personality traits (extraversion, neuroticism, and conscientiousness) assessed by three raters (one selfand two peer raters). Each scale consists of four items (adjectives such as talkative, conscientious, etc.) that were rated on a five-point scale. The sample size is n = 481. Maas, Lensvelt-Mulders, and Hox show in their contribution A multilevel multitrait-multimethod analysis how multilevel models can be applied to analyze MTMM data. Oort presents an application of Three-mode models for multitrait-multimethod data, and Nussbeck, Eid, Geiser, Courvoisier, and Lischetzke show how the data can be analyzed by A CTC(M-1) model for different types of raters. Finally, Hofling, Schermelleh-Engel, and Mossbrugger compare these approaches in their contribution Analysing multitrait-multimethod (MTMM) data: A comparison of three approaches. We hope that the readers will enjoy seeing how this important field of methodological research has developed over the last years.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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