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  • Social scientists often work with theories of reciprocal causality. Sometimes theories suggest that reciprocal causes work simultaneously, or work on a time-scale small enough to make them appear simultaneous. Researchers may employ simultaneous feedback modelsto investigate such theories, although the practice is rare in cross-sectional survey research. This paper discusses the certain conditions that make these models possible if not desirable using such data. This methodological excursus covers the construction of simultaneousfeedback models using a structural equation modeling perspective. This allows the researcher to test if a simultaneous feedback theory fits survey data, test competing hypotheses and engage in macro-comparisons. This paper presents methods in a manner and language amenable to the practicing social scientist who is not a statistician or matrix mathematician. It demonstrates how to run models using three popular software programs (MPlus, Stata and R), and an empirical example using International Social Survey Program data. (xsd:string)
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  • https://doi.org/10.12758/mda.2017.07. (ISSP) (xsd:string)
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  • 2018 (xsd:gyear)
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  • 2018 (xsd:gyear)
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  • 10.12758/mda.2017.07 ()
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  • 43 (xsd:string)
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  • 2190-4936 ()
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  • Simultaneous Feedback Models with Macro-Comparative Cross-Sectional Data (xsd:string)
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  • Bibsonomy (xsd:string)
  • In methods, data, analyses, 12(2), 43, 2018 (xsd:string)
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  • International Social Survey Programme (ISSP) (xsd:string)
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