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      A test of construct isomorphism of the Belief in a Zero-Sum Game scale: A multilevel 43-nation study

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          Abstract

          Background

          We examined the equivalence of the individual and the country-level factor structure of the Belief in a Zero-Sum Game (BZSG) scale, a tool designed to measure antagonistic beliefs about social relations (i.e., perceived social antagonism) in the struggle for limited resources.

          Aims

          In this article we focused on a test of construct isomorphism in a multilevel modeling approach. It was hypothesized that the BZSG measure satisfies all requirements for a strong level of configural isomorphism, and thus that it is useful to investigate BZSG at both the individual and the country levels. The relationships between the BZSG at a country level with other macro-socio-economic indicators were also investigated.

          Method

          Multilevel confirmatory factor analysis (MCFA) was carried out on a cross-country sample composed of 11,368 participants from 43 different countries. We also used the country-level latent BZSG factor in each country as an indicator of a property that we attributed to a particular culture: cultural dimension (collectivism-individualism), macroeconomic indicators (GDP per capita and GNI per capita) and macrosocial indicators (Human Development Index and Democracy Index) describing societies.

          Results

          The results revealed an isomorphic factor structure of perceived social antagonism (measured by BZSG scale), defined in terms of the equivalence factor structure at the both individual and country levels. Furthermore, the relationship between the perceived social antagonism, gross national income per capita, and collectivism were confirmed.

          Conclusions

          Our study supports the usefulness of the BZSG scale for cross-cultural comparison, in the case of its isomorphic structure. At the country level, antagonistic beliefs emerge in hierarchical collectivist societies with lower income. The main contribution of this article is the presentation of the test of construct isomorphism. We made an effort to present a full perspective on construct isomorphism putting together two different but very recent approaches.

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          Most cited references21

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          Universals in the Content and Structure of Values: Theoretical Advances and Empirical Tests in 20 Countries

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            Toward a universal psychological structure of human values.

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              An essay on measurement and factorial invariance.

              Analysis of subgroups such as different ethnic, language, or education groups selected from among a parent population is common in health disparities research. One goal of such analyses is to examine measurement equivalence, which includes both qualitative review of the meaning of items as well as quantitative examination of different levels of factorial invariance and differential item functioning. The purpose of this essay is to review the definitions and assumptions associated with factorial invariance, placing this formulation in the context of bias, fairness, and equity. The connection between the concepts of factorial invariance and item bias (differential item functioning) using a variant of item response theory is discussed. The situations under which different forms of invariance (weak, strong, and strict) are required are discussed. Establishing factorial invariance involves a hierarchy of levels that include tests of weak, strong, and strict invariance. Pattern (metric or weak) factorial invariance implies that the regression slopes are invariant across groups. Pattern invariance requires only invariant factor loadings. Strong factorial invariance implies that the conditional expectation of the response, given the common and specific factors, is invariant across groups. Strong factorial invariance requires that specific factor means (represented as invariant intercepts) also be identical across groups. Strict factorial invariance implies that, in addition, the conditional variance of the response, given the common and specific factors, is invariant across groups. Strict factorial invariance requires that, in addition to equal factor loadings and intercepts, the residual (specific factor plus error variable) variances are equivalent across groups. The concept of measurement invariance that is most closely aligned to that of item response theory considers the latent variable as a common factor measured by manifest variables; the specific factors can be characterized as nuisance variables. Invariance of factor loadings across studied groups is required for valid comparisons of scale score or latent variable means. Strong and strict invariance may be less important in the context of basic research in which group differences in specific factors are indicative of individual differences that are important for scientific exploration. However, for most applications in which the aim is to ensure fairness and equity, strict factorial invariance is required. Health disparities research often focuses on self-reported clinical outcomes such as quality of life that are not observed directly. Latent variable models such as factor analyses are central to establishing valid assessment of such outcomes.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: MethodologyRole: Writing – original draft
                Role: Formal analysisRole: MethodologyRole: SoftwareRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draft
                Role: Formal analysisRole: MethodologyRole: Software
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                28 September 2018
                2018
                : 13
                : 9
                : e0203196
                Affiliations
                [1 ] Institute of Psychology, University of Gdansk, Gdansk, Poland
                [2 ] Department of Psychology, Sapienza University of Rome, Rome, Italy
                Coventry University, UNITED KINGDOM
                Author notes

                Competing Interests: During the time of study, Michal Olech was affiliated with Implicit Explicit Training & Consulting. There are no patents to declare, nor any products in development related to this study. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                http://orcid.org/0000-0003-1131-3910
                Article
                PONE-D-17-42265
                10.1371/journal.pone.0203196
                6162082
                30265677
                d0b929dd-11f2-4860-b745-e314d3489c65
                © 2018 Różycka-Tran et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 6 December 2017
                : 16 August 2018
                Page count
                Figures: 1, Tables: 3, Pages: 15
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100004281, Narodowe Centrum Nauki;
                Award ID: UMO-2017/01/X/HS6/00082
                Award Recipient :
                National Science Center (Poland) funded the costs of publication (2017/01/X/HS6/00082). Michal Olech previously received employment-related income from Implicit Explicit Training & Consulting. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Social Sciences
                Political Science
                Democracy
                Social Sciences
                Sociology
                Culture
                Cross-Cultural Studies
                Social Sciences
                Economics
                Economic Analysis
                Social Sciences
                Sociology
                Culture
                Biology and Life Sciences
                Behavior
                Biology and Life Sciences
                Psychology
                Social Sciences
                Psychology
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Factor Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Factor Analysis
                Social Sciences
                Economics
                Macroeconomics
                Custom metadata
                Data are available in the public repository Open ICPSR ( http://doi.org/10.3886/E103900V1).

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