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      Trust, forgiveness, and peace: The influence of adolescent social identity in a setting of intergroup conflict

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          Abstract

          Following the signing of peace agreements, post-accord societies often remain deeply divided across group lines. There is a need to identify antecedents of youth’s support for peace and establish more constructive intergroup relations. This article explored the effect of out-group trust, intergroup forgiveness, and social identity on support for the peace process among youth from the historic majority and minority communities in Belfast, Northern Ireland. The sample comprised 667 adolescents (49% male; M = 15.74, SD = 1.99 years old) across two time points. The results from the structural equation model suggested that out-group trust was related to intergroup forgiveness over time, while forgiveness related to later support for the peace process. Strength of in-group social identity differentially moderated how out-group trust and intergroup forgiveness related to later support for peace among youth from the conflict-related groups (i.e., Protestants and Catholics). Implications for consolidating peace in Northern Ireland are discussed, which may be relevant to other settings affected by intergroup conflict.

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          Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

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            Structural Equations with Latent Variables

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              Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety.

              Determining sample size requirements for structural equation modeling (SEM) is a challenge often faced by investigators, peer reviewers, and grant writers. Recent years have seen a large increase in SEMs in the behavioral science literature, but consideration of sample size requirements for applied SEMs often relies on outdated rules-of-thumb. This study used Monte Carlo data simulation techniques to evaluate sample size requirements for common applied SEMs. Across a series of simulations, we systematically varied key model properties, including number of indicators and factors, magnitude of factor loadings and path coefficients, and amount of missing data. We investigated how changes in these parameters affected sample size requirements with respect to statistical power, bias in the parameter estimates, and overall solution propriety. Results revealed a range of sample size requirements (i.e., from 30 to 460 cases), meaningful patterns of association between parameters and sample size, and highlight the limitations of commonly cited rules-of-thumb. The broad "lessons learned" for determining SEM sample size requirements are discussed.
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                International Journal of Behavioral Development
                International Journal of Behavioral Development
                SAGE Publications
                0165-0254
                1464-0651
                March 2022
                January 16 2022
                March 2022
                : 46
                : 2
                : 101-111
                Affiliations
                [1 ]University College Dublin, Ireland
                [2 ]Queen’s University Belfast, UK
                [3 ]State University of New York (SUNY Geneseo), USA
                [4 ]Catholic University of America, USA
                [5 ]University of Liverpool, UK
                [6 ]University of Notre Dame, USA
                Article
                10.1177/01650254211066768
                35783662
                2bde0fda-3d77-4ddf-a057-d21d5fc31339
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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