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Making spatial analysis operational: Commands for generating spatial-effect variables in monadic and dyadic data

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Author Info

  • Eric Neumayer

    ()
    (London School of Economics and Political Science)

  • Thomas Plümper

    ()
    (University of Essex)

Abstract

Spatial dependence exists whenever the expected utility of one unit of analysis is affected by the decisions or behavior made by other units of analysis. Spatial dependence is ubiquitous in social relations and interactions. Yet, there are surprisingly few social science studies accounting for spatial dependence. This holds true for settings in which researchers use monadic data, where the unit of analysis is the individual unit, agent, or actor, and even more true for dyadic data settings, where the unit of analysis is the pair or dyad representing an interaction or a relation between two individual units, agents, or actors. Dyadic data offer more complex ways of modeling spatial-effect variables than do monadic data. The commands described in this article facilitate spatial analysis by providing an easy tool for generating, with one command line, spatial-effect variables for monadic contagion as well as for all possible forms of contagion in dyadic data. Copyright 2010 by StataCorp LP.

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Bibliographic Info

Article provided by StataCorp LP in its journal Stata Journal.

Volume (Year): 10 (2010)
Issue (Month): 4 (December)
Pages: 585-605

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Handle: RePEc:tsj:stataj:v:10:y:2010:i:4:p:585-605

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Related research

Keywords: spspc; spundir; spmon; spdir; spagg; spatial dependence; spatial analysis; contagion; spatial lag; spatial error; monadic data; dyadic data;

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