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dc.contributor.authorGill, Jeff
dc.contributor.authorKing, Gary
dc.date.accessioned2010-06-14T14:41:02Z
dc.date.issued2004
dc.identifier.citationGill, Jeff, and Gary King. 2004. What to do when your Hessian is not invertible: Alternatives to model respecification in nonlinear estimation. Sociological Methods and Research 33(1): 54-87.en_US
dc.identifier.issn0049-1241en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4214881
dc.description.abstractWhat should a researcher do when statistical analysis software terminates before completion with a message that the Hessian is not invertable? The standard textbook advice is to respecify the model, but this is another way of saying that the researcher should change the question being asked. Obviously, however, computer programs should not be in the business of deciding what questions are worthy of study. Although noninvertable Hessians are sometimes signals of poorly posed questions, nonsensical models, or inappropriate estimators, they also frequently occur when information about the quantities of interest exists in the data, through the likelihood function. We explain the problem in some detail and lay out two preliminary proposals for ways of dealing with noninvertable Hessians without changing the question asked.en_US
dc.description.sponsorshipGovernmenten_US
dc.language.isoen_USen_US
dc.publisherSAGE Publicationsen_US
dc.relation.isversionofdoi:10.1177/0049124103262681en_US
dc.relation.hasversionhttp://smr.sagepub.com/cgi/content/abstract/33/1/54en_US
dash.licenseLAA
dc.titleWhat to do When Your Hessian is Not Invertible: Alternatives to Model Respecification in Nonlinear Estimationen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalSociological Methods and Researchen_US
dash.depositing.authorKing, Gary
dc.date.available2010-06-14T14:41:02Z
dc.identifier.doi10.1177/0049124103262681*
dash.identifier.orcid0000-0002-5327-7631*
dash.contributor.affiliatedKing, Gary
dc.identifier.orcid0000-0002-5327-7631


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