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1.
The article gives alternatives to Campbell and O'Connell's (1967) definitions of additive and multiplicative method effects in multitrait-multimethod (MTMM) data. The alternative definitions can be formulated by means of constraints in the parameters of the correlated uniqueness (CU) model (Marsh, 1989), which is first reviewed. The definitions have 2 major advantages. First, they allow the researcher to test for additive and multiplicative method effects in a straightforward manner by simply testing the appropriate constraints. An illustration of these tests is given. Second, the alternative definitions are closely linked to other currently used models. The article shows that CU models with additive constraints are equivalent to constrained versions of the confirmatory factor analysis model for MTMM data (Althauser, Heberlein, & Scott, 1971; Werts & Linn, 1970). In addition, Coenders and Saris (1998) showed that, for designs with 3 methods, a CU model with multiplicative constraints is equivalent to the direct product model (Browne, 1984).  相似文献   

2.
In 1959, Campbell and Fiske introduced the use of multitrait–multimethod (MTMM) matrices in psychology, and for the past 4 decades confirmatory factor analysis (CFA) has commonly been used to analyze MTMM data. However, researchers do not always fit CFA models when MTMM data are available; when CFA modeling is used, multiple models are available that have attendant strengths and weaknesses. In this article, we used a Monte Carlo simulation to investigate the drawbacks of either using CFA models that fail to match the data-generating model or completely ignore the MTMM structure of data when the research goal is to uncover associations between trait constructs and external variables. We then used data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development to illustrate the substantive implications of fitting models that partially or completely ignore MTMM data structures. Results from analyses of both simulated and empirical data show noticeable biases when the MTMM data structure is partially or completely neglected.  相似文献   

3.
Geiser, Koch, and Eid (2014) expressed their views on an article we published describing findings from a simulation study and an empirical study of multitrait–multimethod (MTMM) data. Geiser and colleagues raised concerns with (a) our use of the term bias, (b) our statement that the correlated trait–correlated method minus one [CT–C(M–1)] model is not in line with Campbell and Fiske’s (1959) conceptualization of MTMM data, (c) our selection of a data-generating model for our simulation study, and (d) our preference for the correlated trait–correlated method (CT–CM) model over the CT–C(M–1) model. Here, we respond to and elaborate on issues raised by Geiser et al. We maintain our position on each of these issues and point to the interpretational challenges of the CT–C(M–1) model. But, we clarify our opinion that none of the existing structural models for MTMM data are flawless; each has its strengths and each has its weaknesses. We further remind readers of the goal, findings, and implications of our recently published article.  相似文献   

4.
In the past, several models have been developed for the estimation of the reliability and validity of measurement instruments from multitrait-multimethod (MTMM) experiments. Suggestions have been made for additive, multiplicative and correlated uniqueness models, whereas recently Coenders and Saris (2000) suggested a procedure to test these models against one another. In this article, the different models suggested for the analysis of MTMM matrixes have been compared for their fit to 87 data sets collected in the United States (Andrews, 1984; Rodgers, Andrews, & Herzog, 1992), Austria (Koltringer, 1995), and the Netherlands (Scherpenzeel & Saris, 1997). As most variables are categorical, the analysis has been carried out on the basis of polychoric-polyserial correlation coefficients and of Pearson correlations. The fit of the models based on polychoric correlations is much worse than the fit of models based on product moment correlations, but in both cases a model that assumes additive method effects fits most data sets better than the other models, including the so-called multiplicative models.  相似文献   

5.
In a recent article, Castro-Schilo, Widaman, and Grimm (2013) compared different approaches for relating multitrait–multimethod (MTMM) data to external variables. Castro-Schilo et al. reported that estimated associations with external variables were in part biased when either the correlated traits–correlated uniqueness (CT-CU) or correlated traits–correlated (methods–1) [CT-C(M–1)] models were fit to data generated from the correlated traits–correlated methods (CT-CM) model, whereas the data-generating CT-CM model accurately reproduced these associations. Castro-Schilo et al. argued that the CT-CM model adequately represents the data-generating mechanism in MTMM studies, whereas the CT-CU and CT-C(M–1) models do not fully represent the MTMM structure. In this comment, we question whether the CT-CM model is more plausible as a data-generating model for MTMM data than the CT-C(M–1) model. We show that the CT-C(M–1) model can be formulated as a reparameterization of a basic MTMM true score model that leads to a meaningful and parsimonious representation of MTMM data. We advocate the use confirmatory factor analysis MTMM models in which latent trait, method, and error variables are explicitly and constructively defined based on psychometric theory.  相似文献   

6.
Confirmatory factor analysis (CFA) is widely used for analyzing multitrait-multimethod (MTMM) data. But there is no consensus about whether multiplicative or additive trait-method effect of its parameterization, most appropriately represents the underlying structure of MTMM data. Given the popularity of two additive CFA models, the CT-CM model and the CT-CU model, this simulation investigates their performance for multiplicative MTMM data. Results showed that the CT-CM model had much lower convergence and proper solution rates than the CT-CU model. Although both models had adequate fit for the converged solutions, all parameter estimates from the CT-CM model were unacceptably biased. The CT-CU model worked well in most conditions and was quite robust to the multiplicative data when the matrix size was 3T3M.  相似文献   

7.
The classic approach for partitioning and assessing reliability and validity has been through the use of the multitrait-multimethod (MTMM) model. The MTMM approach generally involves 3 different groups (method) evaluating 3 traits. This approach can be reconceptualized for questionnaire evaluation, so that the method becomes 3 different scaling types, which are administered to the same respondents on different occasions to avoid carryover effects. A serious limitation of this MTMM model is that data are required from respondents on at least 3 different occasions, thus placing a heavy burden on the researcher and respondents. Planned incomplete data designs for the purpose of substantially reducing the amount of data required for MTMM models were investigated: 1st, a design that reduces the amount of data collected at the 3rd administration by 22%; and 2nd, a design in which data need only be collected at 2 occasions. The performance of Listwise Deletion, Pairwise Deletion, and the expectation maximization (EM) algorithm at dealing with planned incomplete data are examined through a series of simulations. Results indicate that EM was generally precise and efficient.  相似文献   

8.
In this article we evaluate the psychometric properties of a scale for a perceptual measure of the extent to which manufacturing organizations develop proprietary equipment. We use a confirmatory factor analysis (CFA) approach to assess unidimensionality and reliability as well as convergent, discriminant and concurrent validity. Convergent and discriminant validity is assessed using CFA of the multitrait-multimethod (MTMM) matrix. In addition, we assess the scale's factorial invariance across industries. Results suggest that although method effects are present, the scale demonstrates internal consistency and validity. Implications of this study in the field of operations strategy and general strategy are discussed.  相似文献   

9.
Multiple traits of language proficiency as well as test method effects were concurrently analyzed to investigate interrelations of construct validity, convergent validity, and discriminant validity using multitrait-multimethod (MTMM) matrices. A total of 585 test takers' scores were derived from the field test of the Pearson Test of English Academic. An MTMM confirmatory factor analysis model was parameterized using 4 traits and 3 assessment methods. The 4 traits included listening, reading, speaking, and integrated skills, while the 3 methods included prescribed multiple-choice responses, constructed responses, and summarized responses. The trait factor loadings were systematically greater than those of methods, providing evidence that the indicators were strongly related to their latent constructs, after adjusting for the method effects. The results showed robust convergent validity, moderate discriminant validity, and insignificant method effects. Implications are discussed.  相似文献   

10.
This article compares maximum likelihood and Bayesian estimation of the correlated trait–correlated method (CT–CM) confirmatory factor model for multitrait–multimethod (MTMM) data. In particular, Bayesian estimation with minimally informative prior distributions—that is, prior distributions that prescribe equal probability across the known mathematical range of a parameter—are investigated as a source of information to aid convergence. Results from a simulation study indicate that Bayesian estimation with minimally informative priors produces admissible solutions more often maximum likelihood estimation (100.00% for Bayesian estimation, 49.82% for maximum likelihood). Extra convergence does not come at the cost of parameter accuracy; Bayesian parameter estimates showed comparable bias and better efficiency compared to maximum likelihood estimates. The results are echoed via 2 empirical examples. Hence, Bayesian estimation with minimally informative priors outperforms enables admissible solutions of the CT–CM model for MTMM data.  相似文献   

11.
Multitrait-multimethod (MTMM) analyses are used in psychology to assess convergent and discriminant validity and to study method effects. Most current MTMM approaches assume that measures have equal convergent and discriminant validity across the entire range of trait values and thus do not account for potential trait × method interactions. A novel approach is presented that allows analyzing trait × method interactions using factor mixture modeling. The new MTMM mixture model allows identifying latent classes of individuals who differ with respect to convergent and discriminant validity. The new approach was applied to mother’s and father’s ratings of children’s attention deficit hyperactivity disorder (ADHD) symptoms (N = 618). Results revealed four latent classes: one with no symptom levels, two with low symptom levels, and one with moderate symptom levels. Three classes showed evidence for convergent and discriminant validity, whereas a low symptom class lacked convergent validity for ratings of inattention.

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12.
This article examines 4 approaches for explaining shared method variance, each applied to a longitudinal trait–state–occasion (TSO) model. Many approaches have been developed to account for shared method variance in multitrait-multimethod (MTMM) data. Some of these MTMM approaches (correlated method, orthogonal method, correlated method minus one, correlated uniqueness) were therefore borrowed in these analyses such that their effectiveness could be evaluated in conjunction with a TSO model. To this end, datasets were generated according to 4 different covariance matrices (each created according to specifications of a model built with 1 of the 4 approaches) and each model was crossed with each type of data. Whereas the correlated method and correlated method minus one approaches encountered many difficulties in convergence, fit, or parameter estimates, the correlated uniqueness and orthogonal method approaches proved to be quite versatile.  相似文献   

13.
本文主要利用矩阵模型对两个有限自动机的限制直积进行讨论,在此基础上对限制直积的状态映射矩阵和输出映射矩阵进行了研究,并给出了它们的一些性质.  相似文献   

14.
While focusing on Democracy and Education, James Campbell attempts in this essay to offer a synthesis of the full range of John Dewey's educational thought. Campbell explores in particular Dewey's understanding of the relationship between democracy and education by considering both his ideas on the reconstruction of education and on the role of education in broader social reconstruction. Throughout his philosophical work, Campbell concludes, Dewey offers us a vision of a society self‐consciously striving to enable its members to live fully educative lives.  相似文献   

15.
The following essay provides an analysis of the rhetorical strategies employed by Leonora O'Reilly, a Progressive Era labor reformer. The essay argues that O'Reilly's use of enactment and empowerment are representative of a “feminine style” as defined by Campbell (1989) and extended by Dow and Tonn (1993). As a subject of analysis, O'Reilly's rhetoric provides an opportunity to examine the public voice of a working‐class female reformer.  相似文献   

16.
We introduce an approach for ensuring empirical identification of the correlated trait–correlated method (CT–CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait–correlated method (ACT–CM) models because they are based on systematically augmenting the multitrait–multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT–CM model, but a well-identified fully augmented correlated trait–correlated method (FACT–CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor—a specific case shown to lead to an empirically underidentified CT–CM model.  相似文献   

17.
Ipsative data (individual scores subject to a constant-sum constraint), suggested to minimize response bias, are sometimes observed in behavioral sciences. Chan and Bentler (1993, 1996) proposed a method to analyze ipsative data in a single-group case. Cheung and Chan (2002) extended the method to multiple-group analysis. However, these methods require tedious procedures on formulating within- and between-group constraints and recovering the parameter estimates and their standard errors. A direct estimation method, which is equivalent to Chan and Bentler's method with an alternative model specification, is proposed in this article. The 1st-order factor-analytic ipsative model in Chan and Bentler's method is reparameterized as a restricted 2nd-order factor-analytic model with fixed factor loading matrix reflecting the ipsative properties in the direct estimation method. The direct estimation method can be easily extended to test measurement invariance properties in multiple-group analysis. Issues related to ipsative models are also addressed.  相似文献   

18.
This study compared the Developmental Indicators for the Assessment of Learning—Revised (DIAL-R) and the Learning Accomplishment Profile—Diagnostic (LAP-D) for a sample of 121 children in an urban Head Start program. To examine validity, guidelines suggested by the multitrait-multimethod model (MTMM) were employed. The results indicated significant correlations between like-named scales, providing evidence for convergent validity. However, the within-method correlations often equaled or exceeded the validity coefficients, as did the between-method correlations of dissimilar scales. Thus the simultaneous requirements of both convergent and discriminant validity were not met. From the viewpoint of professional practices, the results suggest that profiles cannot be interpreted with confidence. New instruments and procedures are needed that reflect research and theory associated with the principles of psychosocial Change.  相似文献   

19.
This study examined the concurrent validity of the composite and area scores of the Stanford-Binet Intelligence Scale: Fourth Edition (SBIV) and the Mental Processing Composite and global scale scores of the Kaufman Assessment Battery for Children (K-ABC). The tenability of interpreting the SBIV using the fluid/crystallized model, as suggested by the authors, was also considered. The subjects were 30 Black, learning-disabled elementary school students. Results of a t test indicated that the Mental Processing Composite score of the K-ABC was significantly higher than the SBIV Composite score. Moderate to high correlations were obtained when SBIV composite and area scores were compared to K-ABC composite and scale scores, reflecting a positive relationship between the two tests. The measures of fluid abilities (K-ABC Composite score; SBIV Abstract/Visual Reasoning) were highly correlated. The results of a multiple regression analysis indicated a moderate degree of correlation among the measures of crystallized ability (K-ABC Achievement; SBIV Verbal Reasoning and Quantitative Reasoning). The findings of this study demonstrated adequate concurrent validity for the SBIV. In addition, the results provided limited support for describing test results utilizing the fluid/crystallized interpretation model. Further research is suggested in order to examine other validity issues, such as classification of special education students and the SBIV's relationship to other similar instruments.  相似文献   

20.
Multisource feedback instruments are a widely used tool in human resource management. However, comprehensive validation studies remain scarce and there is a lack of statistical models that account appropriately for the complex data structure. Because both peers and subordinates are nested within the target but stem from different populations, the assumption of traditional multilevel structural equation models that the sample on a lower level stems from the same population is violated. We present a multilevel confirmatory factor analysis multitrait–multimethod (ML–CFA–MTMM) model that considers this peculiarity of multisource feedback instruments. The model is applied to 2 scales of the Benchmarks® instrument and it is demonstrated how measures of reliability and of convergent and discriminant validity can be obtained using multilevel structural equation modeling software. We discuss the results as well as some implications and guidelines for the use of the model.  相似文献   

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