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Dyadic Regression in the Presence of Heteroscedasticity: An Assessment of Alternative Approaches
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Government.
2010 (English)In: Social Networks, ISSN 0378-8733, E-ISSN 1879-2111, Vol. 32, no 4, 279-289 p.Article in journal (Refereed) Published
Abstract [en]

Although the problem of heteroscedasticity has been the subject of much discussion in other areas of applied statistics the problem has received scant attention in the social network literature. This study attempts to remedy this situation by considering how traditional methods for significance testing in dyadic regression models, such as standard QAP tests, perform under conditions of heteroscedasticity. Moreover, the article presents two alternative methods to deal with heteroscedasticity that are both shown to perform rather well with typical social network data under conditions of both heteroscedasticity and homoscedasticity. Overall, the results of the study suggest that applied researchers using regression techniques to study dyadic data are well advised to correct for heteroscedasticity, by either of the two methods discussed here, whenever there is a reason to suspect heteroscedasticity.

Place, publisher, year, edition, pages
Elsevier , 2010. Vol. 32, no 4, 279-289 p.
Keyword [en]
Dyadic regression; Quadratic assignment; Autocorrelation; Heteroscedasticity; Two-way clustered standard errors
National Category
Political Science (excluding Public Administration Studies and Globalization Studies)
Identifiers
URN: urn:nbn:se:uu:diva-131053DOI: 10.1016/j.socnet.2010.04.002ISI: 000283402000003OAI: oai:DiVA.org:uu-131053DiVA: diva2:352663
Available from: 2010-09-22 Created: 2010-09-22 Last updated: 2017-12-12Bibliographically approved

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Lindgren, Karl-Oskar

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