{"title":"The Multitrait-Multimethod Matrix at 50!","authors":"M. Eid, Fridtjof W. Nussbeck","doi":"10.1027/1614-2241.5.3.71","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2009-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1027/1614-2241.5.3.71","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 36
Abstract
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.