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      Domain-Specific Greed

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          Abstract

          Greed, the insatiable and excessive desire and striving for more even at the expense of others, may be directed toward various goods. In this article, we propose that greed may be conceptualized as a domain-specific construct. Based on a literature review and an expert survey, we identified 10 domains of greed which we operationalized with the DOmain-SPEcific Greed (DOSPEG) questionnaire. In Study 1 ( N = 725), we found support for the proposed structure and convergent validity with related constructs. Bifactor-(S-1) models revealed that generic greed is differentially related to the greed domains, indicating that generic greed primarily captures a striving for money and material things. In the second study ( N = 591), we found that greed domains had incremental validity beyond generic greed with regard to corresponding criteria assessed via self- and other-reports. We conclude that greed can be conceptualized as a domain-specific construct and propose an onion model reflecting this structure.

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          G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

          G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of the t, F, and chi2 test families. In addition, it includes power analyses for z tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.
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            lavaan: AnRPackage for Structural Equation Modeling

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              From alpha to omega: a practical solution to the pervasive problem of internal consistency estimation.

              Coefficient alpha is the most popular measure of reliability (and certainly of internal consistency reliability) reported in psychological research. This is noteworthy given the numerous deficiencies of coefficient alpha documented in the psychometric literature. This mismatch between theory and practice appears to arise partly because users of psychological scales are unfamiliar with the psychometric literature on coefficient alpha and partly because alternatives to alpha are not widely known. We present a brief review of the psychometric literature on coefficient alpha, followed by a practical alternative in the form of coefficient omega. To facilitate the shift from alpha to omega, we also present a brief guide to the calculation of point and interval estimates of omega using a free, open source software environment. © 2013 The British Psychological Society.
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Personality and Social Psychology Bulletin
                Pers Soc Psychol Bull
                SAGE Publications
                0146-1672
                1552-7433
                January 25 2023
                : 014616722211480
                Affiliations
                [1 ]University Hospital Würzburg, Germany
                [2 ]Freie Universität Berlin, Germany
                [3 ]Universität Augsburg, Germany
                [4 ]Julius-Maximilians-Universität Würzburg, Germany
                Article
                10.1177/01461672221148004
                ec695b3b-67cd-472f-9f55-f4e30213e556
                © 2023

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

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