A Critique of Dyadic Design.
Dyadic research designs concern data that comprise interactions among actors. They are, without a doubt, the most frequent designs employed in the empirical analysis of international politics. But what do such designs carry with them in terms of theoretical claims and statistical problems? These two...
| Publicado en: | International Studies Quarterly Vol. 60; no. 2; pp. 355 - 363 |
|---|---|
| Autores principales: | , |
| Formato: | Essay |
| Publicado: |
Oxford University Press / USA
Jun2016
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=117242497&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 117242497 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00208833 ISQ jtl: International Studies Quarterly issn: 00208833 maglogo: N pubinfo: dt: Jun2016 vid: 60 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 117242497 10.1093/isq/sqw007 ppf: 355 ppct: 8 formats: fmt: @attributes: type: P db: hlh ui: 117242497 tig: atl: A Critique of Dyadic Design. aug: au: CRANMER, SKYLER J. DESMARAIS, BRUCE A. affil: The Ohio State University Pennsylvania State University su: Dyadic analysis (Social sciences) International relations research Social network theory Experimental design Mathematical variables Statistical models Statistical research Research bias sug: subj: Dyadic analysis (Social sciences) International relations research Social network theory International Affairs Foreign affairs Experimental design Mathematical variables Statistical models Statistical research Research bias ab: Dyadic research designs concern data that comprise interactions among actors. They are, without a doubt, the most frequent designs employed in the empirical analysis of international politics. But what do such designs carry with them in terms of theoretical claims and statistical problems? These two issues closely intertwine. When testing hypotheses empirically, the statistical model must be a careful operationalization of the theory under consideration. Given that the theoretical and statistical cannot be separated, we discuss dyadic research designs from these two perspectives. We highlight problems of model misspecification, erroneous assumptions about the independence of events, artificial levels of analysis, and the incoherent treatment of multilateral/ multiparty events on the theoretical side. On the statistical side, we stress difficult-to-escape challenges to valid inference. pubtype: Academic Journal doctype: Essay src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
|---|