Reflective measurement models, behavior domains, and common causes

AbstractPartial least squares path modeling (PLS-PM) has become very popular in recent years, for measuring concepts that depend on different aspects and that are based on different types of relationships. PLS-PM represents a useful tool to explore relationships and to analyze the influence of the different aspects on the complex phenomenon analyzed. In particular, the use of higher-order constructs has allowed researchers to extend the application of PLS-PM to more advanced and complex models. In this work, our attention is focused on higher-order constructs that include reflective or formative relationships. Even if the dispute between formative models and reflective models is not exactly recent, it is still alive in current literature, for the most part within the context of structural equation models. This paper focuses attention on theoretical and mathematical differences between formative and reflective measurement models within the context of the PLS-PM approach. A simulation study is proposed in order to show how these approaches fit well in different modeling situations. The approaches have been compared using empirical application in a sustainability context. The findings from the simulation and the empirical application can help researchers to estimate and to use the higher-order PLS-PM approach in reflective and formative type models.

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Evaluation of Reflective Measurement Models

10.1007/978-3-030-80519-7_4 ◽

2021 ◽

pp. 75-90

Author(s):

Joseph F. Hair ◽

G. Tomas M. Hult ◽

Christian M. Ringle ◽

Marko Sarstedt ◽

Nicholas P. Danks ◽

...

Keyword(s):

Convergent Validity ◽

Discriminant Validity ◽

Reliability And Validity ◽

Internal Consistency Reliability ◽

Measurement Model ◽

Path Model ◽

Model Assessment ◽

Measurement Models ◽

Reflective Measurement ◽

Composite Reliability

AbstractThe goal of reflective measurement model assessment is to ensure the reliability and validity of the construct measures and therefore provides support for the suitability of their inclusion in the path model. This chapter introduces the key criteria that are relevant in reflective measurement model assessment: indicator reliability, internal consistency reliability (Cronbach’s alpha, reliability coefficient rhoA, and composite reliability rhoC), convergent validity, and discriminant validity. We illustrate their use by means of the SEMinR package and a well-known model on corporate reputation.

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Assessment of Readiness and Usability of Information Systems Use

Jurnal Online Informatika ◽

10.15575/join.v4i1.256 ◽

2019 ◽

Vol 4 (1) ◽

pp. 1

Author(s):

Dwi Yuniarto ◽

A’ang Subiyakto ◽

Aedah Binti Abd. Rohman ◽

Reny Rian Marliana

Keyword(s):

Information Systems ◽

Convergent Validity ◽

Discriminant Validity ◽

Structural Model ◽

Internal Consistency Reliability ◽

Integration Model ◽

Measurement Models ◽

Reliability Indicator ◽

Information Systems Use ◽

Reflective Measurement

The assessment of the use of information systems has been carried out by many researchers. This research was conducted in Private Universities in Indonesia, which currently involve many information systems in many ways, especially those related to the management of Higher Education, by measuring the readiness and usability of the use of information systems with models that I build from the integration of two models. The results of the measurement of this study were obtained from the distribution of questionnaires, there were 47% of respondents who filled 61-80% of the level of IS usage and 68% of respondents stated their readiness in the level of readiness to use IS. The stage consists of evaluating reflective measurement models and structural model assessments. Evaluating reflective measurement in evaluating internal consistency reliability using Composite Reliability, Reliability Indicator, Convergent Validity, and Discriminant Validity, finally concluded that the use of the Readiness and Usability integration model can be forwarded to a more complex research stage and can use the questionnaire.

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Formative and reflective measurement models for analysing transit service quality

Public Transport ◽

10.1007/s12469-017-0168-9 ◽

2017 ◽

Vol 10 (1) ◽

pp. 107-127 ◽

Cited By ~ 10

Author(s):

Laura Eboli ◽

Carmen Forciniti ◽

Gabriella Mazzulla

Keyword(s):

Service Quality ◽

Transit Service ◽

Measurement Models ◽

Reflective Measurement

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Formative versus reflective measurement models: Two applications of formative measurement

Journal of Business Research ◽

10.1016/j.jbusres.2008.01.013 ◽

2008 ◽

Vol 61 (12) ◽

pp. 1250-1262 ◽

Cited By ~ 487

Author(s):

Tim Coltman ◽

Timothy M. Devinney ◽

David F. Midgley ◽

Sunil Venaik

Keyword(s):

Formative Measurement ◽

Measurement Models ◽

Reflective Measurement

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FACT-2 – The Frankfurt Adaptive Concentration Test

European Journal of Psychological Assessment ◽

10.1027/1015-5759.25.2.73 ◽

2009 ◽

Vol 25 (2) ◽

pp. 73-82 ◽

Cited By ~ 9

Author(s):

Frank Goldhammer ◽

Helfried Moosbrugger ◽

Sabine A. Krawietz

Keyword(s):

Convergent Validity ◽

Four Dimensions ◽

Measurement Models ◽

Cognitive Failures ◽

Concentration Test ◽

Cognitive Failures Questionnaire

The Frankfurt Adaptive Concentration Test (FACT-2) requires discrimination between geometric target and nontarget items as quickly and accurately as possible. Three forms of the FACT-2 were constructed, namely FACT-I, FACT-S, and FACT-SR. The aim of the present study was to investigate the convergent validity of the FACT-SR with self-reported cognitive failures. The FACT-SR and the Cognitive Failures Questionnaire (CFQ) were completed by 191 participants. The measurement models confirmed the concentration performance, concentration accuracy, and concentration homogeneity dimensions of FACT-SR. The four dimensions of the CFQ (i.e., memory, distractibility, blunders, and names) were not confirmed. The results showed moderate convergent validity of concentration performance, concentration accuracy, and concentration homogeneity with two CFQ dimensions, namely memory and distractibility/blunders.

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Forced Zero Cross-Loading Misspecifications in Measurement Component of Structural Equation Models

Methodology ◽

10.1027/1614-2241/a000084 ◽

2014 ◽

Vol 10 (4) ◽

pp. 138-152 ◽

Cited By ~ 5

Author(s):

Hsien-Yuan Hsu ◽

Susan Troncoso Skidmore ◽

Yan Li ◽

Bruce Thompson

Keyword(s):

Structural Equation ◽

Structural Model ◽

Structural Equation Models ◽

Equation Model ◽

Model Fit ◽

Model Specification ◽

Simulation Design ◽

Measurement Models ◽

Fit Statistics ◽

Path Coefficients

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.

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