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      How does ingroup identification predict forgiveness in post‐conflict societies? The role of conflict narratives

      1 , 2 , 3 , 2
      British Journal of Social Psychology
      Wiley

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          Abstract

          People's religious identity is often the central identity in many ethnopolitical conflicts. These identities in conflict contexts may be associated with how people see conflict and their willingness to forgive the outgroup members for their wrongdoings in the past. Study 1 ( N = 287) tested how religious group identification in the Northern Irish context predicted forgiveness through the endorsement of dominant conflict narratives (i.e., terrorism and independence narratives) among Protestants and Catholics. We also tested how group membership may moderate these relationships. The results showed that among Protestants, higher Protestant identification predicted less forgiveness through higher endorsement of the terrorism narrative and less endorsement of the independence narrative. Among Catholics, on the other hand, higher Catholic identification predicted stronger endorsement of the independence narrative, and in turn, less forgiveness. Study 2 ( N = 526) aimed to replicate the findings of Study 1 with a larger sample and extend them by testing the role of an alternative conflict narrative (i.e., the Northern Irish identity narrative). The results were largely replicated for the independence and terrorism narratives, and the Northern Irish identity narrative was associated with higher forgiveness across both groups. We discuss the results in terms of how ingroup identities and conflict narratives can become both facilitators of and barriers to peacebuilding in post‐conflict societies.

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          Framing: Toward Clarification of a Fractured Paradigm

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            Bias in cross-sectional analyses of longitudinal mediation.

            Most empirical tests of mediation utilize cross-sectional data despite the fact that mediation consists of causal processes that unfold over time. The authors considered the possibility that longitudinal mediation might occur under either of two different models of change: (a) an autoregressive model or (b) a random effects model. For both models, the authors demonstrated that cross-sectional approaches to mediation typically generate substantially biased estimates of longitudinal parameters even under the ideal conditions when mediation is complete. In longitudinal models where variable M completely mediates the effect of X on Y, cross-sectional estimates of the direct effect of X on Y, the indirect effect of X on Y through M, and the proportion of the total effect mediated by M are often highly misleading. (c) 2007 APA, all rights reserved.
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              Principled missing data methods for researchers

              The impact of missing data on quantitative research can be serious, leading to biased estimates of parameters, loss of information, decreased statistical power, increased standard errors, and weakened generalizability of findings. In this paper, we discussed and demonstrated three principled missing data methods: multiple imputation, full information maximum likelihood, and expectation-maximization algorithm, applied to a real-world data set. Results were contrasted with those obtained from the complete data set and from the listwise deletion method. The relative merits of each method are noted, along with common features they share. The paper concludes with an emphasis on the importance of statistical assumptions, and recommendations for researchers. Quality of research will be enhanced if (a) researchers explicitly acknowledge missing data problems and the conditions under which they occurred, (b) principled methods are employed to handle missing data, and (c) the appropriate treatment of missing data is incorporated into review standards of manuscripts submitted for publication.
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                Author and article information

                Journal
                British Journal of Social Psychology
                British J Social Psychol
                Wiley
                0144-6665
                2044-8309
                April 2023
                November 25 2022
                April 2023
                : 62
                : 2
                : 910-931
                Affiliations
                [1 ] School of Psychology University of Sussex Falmer UK
                [2 ] Department of Psychological and Brain Sciences University of Massachusetts Amherst Amherst Massachusetts USA
                [3 ] School of Psychology Queen's University Belfast Belfast UK
                Article
                10.1111/bjso.12608
                36426991
                7325f11b-b2d8-4b35-84c7-6bc6d3f39892
                © 2023

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

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