Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-22T03:37:58.941Z Has data issue: false hasContentIssue false
  • English
  • Français

Networks, Dyads, and the Social Relations Model*

Published online by Cambridge University Press:  08 November 2013

Cassy Dorff  and
Michael D. Ward
Get access Rights & Permissions [Opens in a new window]

Abstract

Quantitative international relations scholarship has focused on analysis of the so-called dyad. Few studies have given serious thought to the definition of a dyad, or to the implications that flow from such a conceptualization. This article argues that the current approach to dyadic analysis is necessarily incomplete and at times induces incoherent pictures of the ebb and flow of interactions among actors in global politics and economics. It presents the Social Relations Model as a systematic way of analyzing the dependencies inherent in dyadic data. The study uses this model to examine militarized interstate disputes from 1816 to 2001, the trade network of 2000 and reciprocity between enemies in the treatment of prisoners of war.

Type
Original Articles
Information
Political Science Research and Methods , Volume 1 , Issue 2 , December 2013 , pp. 159 - 178
Copyright
Copyright © The European Political Science Association 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

Cassy Dorff is a PhD Candidate in the Department of Political Science, Duke University, Durham, NC, USA, 27707 ([email protected]). Michael D. Ward is a Professor in the Department of Political Science, Duke University, Durham, NC, USA, 27707 ([email protected]). We thank our lab colleagues at Duke for feedback and comments, especially Nils Metternich, Andreas Beger, & Florian Hollenbach. All mistakes are our own.

References

Beck, Neal. 2012. Sweeping Fewer Things under the Rug: Tis Often (Usually?) Better to Model than Be Robust. Paper presented at the Society for Political Methodology POLMETH XXIX conference, 18–21 July, University of North Carolina at Chapel Hill, United States.Google Scholar
Bennett, D. ScottStam, Allan C.. 2000. ‘Research Design and Estimator Choices in the Analysis of Interstate Dyads: When Decisions Matter’. Journal of Conflict Resolution 44(5):653–685.CrossRefGoogle Scholar
Bond, Charles F.Lashley, Brian R.. 1996. ‘Round-robin Analysis of Social Interaction: Exact and Estimated Standard Errors’. Psychometrika 61(2):303–311.Google Scholar
Bremer, Stuart A. 1992. ‘Dangerous Dyads: Conditions Affecting the Likelihood of Interstate War, 1816–1965’. The Journal of Conflict Resolution 36(2):309–341.Google Scholar
Breunig, Christian, Cao, XunLuedtke, Adam. 2012. ‘Global Migration and Political Regime Type: A Democratic Disadvantage’. British Journal of Political Science 42(4):825–854.Google Scholar
Cao, Xun. 2009. ‘Networks of Intergovernmental Organizations and Convergence in Domestic Economic Policies’. International Studies Quarterly 53(4):1095–1130.CrossRefGoogle Scholar
Caplow, Theodore. 1956. ‘A Theory of Coalitions in the Triad’. American Sociological Review 21(4):489–493.Google Scholar
Card, Noel A., Selig, James P.Little, Todd D., eds. 2008. Modeling Dyadic and Interdependent Data in the Developmental and Behavioral Sciences. New York: Routledge.Google Scholar
Cranmer, Skyler J., Desmarais, Bruce A.Elizabeth, J.M.. 2012. ‘Complex Dependencies in the Alliance Network’. Conflict Management and Peace Science 29(3):279–313.Google Scholar
Cunningham, David, Gleditsch, Kristian SkredeSalehyan, Idean. 2009. ‘It Takes Two: A Dyadic Analysis of Civil War Duration and Outcome’. Journal of Conflict Resolution 53(4):570–597.Google Scholar
Dafoe, Allan, Oneal, John R.Russett, Bruce M.. 2013. ‘The Democratic Peace: Weighing the Evidence and Cautious Inference’. International Studies Quarterly 57(1):201–214.CrossRefGoogle Scholar
Elkins, Zachary, Guzman, Andrew T.Simmons, Beth A.. 2006. ‘Competing for Capital: The Diffusion of Bilateral Investment Treaties, 1960–2000’. International Organization 60(4):811–846.Google Scholar
Fisher, Ronald A. 1925. Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.Google Scholar
Gabriel, Kuno Ruben. 1998. ‘Generalised Bilinear Regression’. Biometrika 85(3):689–700.Google Scholar
Gartzke, Erik A.Gleditsch, Kristian Skrede. 2004. ‘Regime Type and Commitment: Why Democracies Are Actually Less Reliable Allies’. American Journal of Political Science 48(4):775–795.Google Scholar
Gartzke, ErikWeisiger, Alex. 2013. ‘Permanent Friends? Dynamic Difference and the Democratic Peace’. International Studies Quarterly 57(1):171–185.Google Scholar
Gasiorowski, Mark J.Polachek, Soloman W.. 1982. ‘Conflict Interdependence: East-West Trade and Linages in the Era of Détente’. Journal of Conflict Resolution 26(4):709–729.CrossRefGoogle Scholar
Gill, Paramjit S.Swartz, Tim B.. 2001. ‘Statistical Analyses for Round Robin Interaction Data’. The Canadian Journal of Statistics. La Revue Canadienne de Statistique 29(2):321–331.CrossRefGoogle Scholar
Goldstein, Joshua S.Freeman, John R.. 1990. Three Way Street: Strategic Reciprocity in World Politics. Chicago, IL: University of Chicago Press.Google Scholar
Hays, Jude C., Kachi, AyaFranzese, Robert J.. 2010. ‘A Spatial Model Incorporating Dynamic, Endogenous Network Interdependence: A Political Science Application’. Statistical Methodology 7(3):406–428.Google Scholar
Hill, Daniel W. Jr., Ward, Michael D.. 2013. ‘Reciprocity, Democracy, and Transgressions of the Laws of War’. unpublished manuscript, available at http://mdwardlab.com/biblio/reciprocity-democracy-and-transgressions-laws-war.Google Scholar
Hoff, Peter D. 2005. ‘Bilinear Mixed Effects Models for Dyadic Data’. Journal of the American Statistical Association 100:286–295.Google Scholar
Hoff, Peter D., Raftery, Adrian E.Handcock, Mark S.. 2002. ‘Latent Space Approaches to Social Network Analysis’. Journal of the American Statistical Association 97(460):1090–1098.Google Scholar
Hoff, Peter D., Fosdick, Bailey., Volfovsky, Alex, Stovel, Katherine. 2012. ‘Likelihoods for Fixed Rank Nomination Networks’. arXive-stat:me (arXiv:1212.6234).CrossRefGoogle Scholar
Hoff, Peter D.Ward, Michael D.. 2004. ‘Modeling Dependencies in International Relations Networks’. Political Analysis 12(2):160–175.Google Scholar
Kaplan, Morton A. 1957. System and Process in International Politics. New York: John Wiley and Sons.Google Scholar
Kenny, David A. 1981. ‘Interpersonal Perception: A Multivariate Round Robin Analysis’. In Scientific Inquiry and the Social Sciences: A Volume in Honor of Donald T. Campbell, edited by Marilynn B. Brewer and Barry E. Collins, 288–309. San Francisco, CA: Jossey-Bass.Google Scholar
Kenny, David A.. 1994. Interpersonal Perception: A Social Relations Analysis. New York: Guilford Press.Google Scholar
Kenny, David A., Kashy, Deborah A.Cook, William L.. 2006. Dyadic Data Analysis. New York: Guilford Press.Google Scholar
King, Gary. 2001. ‘Proper Nouns and Methodological Propriety: Pooling Dyads in International Relations Data’. International Organization 55(2):497–507.Google Scholar
King, Gary, Roberts, Molly. 2012. How Robust Standard Errors Expose Methodological Problems They Do Not Fix. Paper presented at the Society for Political Methodology POLMETH XXIX conference, 18–21 July, University of North Carolina at Chapel Hill, United States.Google Scholar
Kolaczyk, Eric D. 2009. Statistical Analysis of Network Data: Methods and Models. Berlin: Springer Verlag.Google Scholar
Krivitsky, PavelHandcock, Mark S.. 2008. ‘Fitting Latent Cluster Models for Social Networks with Latentnet’. Journal of Statistical Software 24(5):1–23.Google Scholar
Lemke, DouglasReed, William. 2001. ‘The Relevance of Politically Relevant Dyads’. The Journal of Conflict Resolution 45(1):126–144.Google Scholar
Li, HengLoken, Eric. 2002. ‘A Unified Theory of Statistical Analysis and Inference for Variance Component Models For Dyadic Data’. Statistica Sinica 12(2):519–535.Google Scholar
Malloy, Thomas E.Kenny, David A.. 1986. ‘The Social Relations Model: An Integrative Method for Personality Research’. Journal of Personality 54(1):199–225.Google Scholar
Maoz, ZeevRussett, Bruce M.. 1993. ‘Normative and Structural Causes of Democratic Peace, 1946–1986’. American Political Science Review 87(3):624–638.Google Scholar
McClelland, Charles A. 1967. Theory of the International System. New York: Macmillan Publishing Company.Google Scholar
Metternich, Nils, Dorff, Cassy, Gallop, Max, Weschle, SimonWard, Michael D.. 2013. ‘Anti-government Networks in Civil Conflicts’. American Journal of Political Science forthcoming.Google Scholar
Morgenthau, Hans J. 1948. Politics Among Nations. New York: McGraw-Hill.Google Scholar
Morrow, James D. 2007. ‘When do States Follow the Laws of War?’ American Political Science Review 101(03):559–572.Google Scholar
Morrow, James D.Jo, Hyeran. 2006. ‘Compliance with the Laws of War: Dataset and Coding Rules’. Conflict Management and Peace Science 23(1):91–113.Google Scholar
Morse, Philip M.Feshbach, Herman. 1953. Methods of Theoretical Physics, Vol. 1. New York: McGraw-Hill.Google Scholar
Mousseau, Michael. 2013. ‘The Democratic Peace Unraveled: It's the Economy’. International Studies Quarterly 57(1):186–197.Google Scholar
Neumayer, EricPlümper, Thomas. 2010. ‘Spatial Effects in Dyadic Data’. International Organization 64(1):145–166.Google Scholar
Poast, Paul. 2010. ‘(Mis)Using Dyadic Data to Analyze Multilateral Events’. Political Analysis 18(4):403–425.Google Scholar
Rajmaira, SheenWard, Michael D.. 1990. ‘Evolving Foreign Policy Norms: Reciprocity in the Superpower Triad’. International Studies Quarterly 34:457–475.Google Scholar
Reuveny, RafaelLi, Quan. 2003. ‘The Joint Democracy-Dyadic Conflict Nexus: A Simultaneous Equations Model’. International Studies Quarterly 47(3):325–346.Google Scholar
Rose, Andrew K. 2007. ‘Do We Really Know that the WTO Increases Trade? Reply’. The American Economic Review 97:2019–2025.Google Scholar
Rousseau, David, Gelpi, Christopher, Reiter, DanHuth, Paul. 1996. ‘Assessing the Dyadic Nature of the Democratic Peace, 1918–1988’. American Political Science Review 90(3):512–533.Google Scholar
Russett, Bruce M., Oneal, John R.Davis, David R.. 1998. ‘The Third Leg of the Kantian Tripod for Peace: International Organizations and Militarized Disputes, 1950–1985’. International Organization 52:441–468.CrossRefGoogle Scholar
Salehyan, IdeanGleditsch, Kristian Skrede. 2006. ‘Refugee Flows and the Spread of Civil War’. International Organization 60(2):335–336.Google Scholar
Simmel, Georg. 1908. Soziologie. Leipzig, Germany: Duncker and Humblot.Google Scholar
Snijders, Tom A.B.Kenny, David A.. 1999. ‘The Social Relations Model for Family Data: S Multilevel Approach’. Personal Relationships 6(4):471–486.Google Scholar
Tomz, Michael, Goldstein, JudithRivers, Douglas. 2007. ‘Do We Really Know That the WTO Increases Trade? Comment’. American Economic Review 97(5):2005–2018.Google Scholar
Tönnies, Ferdinand. 1887. Gemeinschaft und Gesellschaft. Leipzig, Germany: Fues Verlag.Google Scholar
Ward, Michael D., Ahlquist, John S.Rozenas, Arturas. 2013. ‘Gravitiy's Rainbow: Modeling the World Trade Network’. Network Science 1(1):95–118.Google Scholar
Ward, Michael D.Hoff, Peter D.. 2007. ‘Persistent Patterns of International Commerce’. Journal of Peace Research 44(2):157–175.Google Scholar
Ward, Michael D., Siverson, Randolph M.Cao, Xun. 2007. ‘Disputes, Democracies, and Dependencies: A Reexamination of the Kantian Peace’. American Journal of Political Science 51(3):583–601.Google Scholar
Warner, Rebecca, Kenny, David A.Stoto, Michael A.. 1979. ‘A New Round Robin Analysis of Variance for Social Interaction Data’. Journal of Personality and Social Psychology 37:1742–1757.Google Scholar
Wasserman, StanleyFaust, Katherine. 1994. Social Network Analysis: Methods and Applications. Cambridge: Cambridge University Press.Google Scholar