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Extensions of the Penalized Spline of Propensity Prediction Method of Imputation

dc.contributor.authorZhang, Guangyuen_US
dc.contributor.authorLittle, Roderick J. A.en_US
dc.date.accessioned2010-04-01T14:44:46Z
dc.date.available2010-04-01T14:44:46Z
dc.date.issued2009-09en_US
dc.identifier.citationZhang, Guangyu; Little, Roderick (2009). "Extensions of the Penalized Spline of Propensity Prediction Method of Imputation." Biometrics 65(3): 911-918. <http://hdl.handle.net/2027.42/65192>en_US
dc.identifier.issn0006-341Xen_US
dc.identifier.issn1541-0420en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/65192
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=19053998&dopt=citationen_US
dc.description.abstractLittle and An (2004,  Statistica Sinica   14, 949–968) proposed a penalized spline of propensity prediction (PSPP) method of imputation of missing values that yields robust model-based inference under the missing at random assumption. The propensity score for a missing variable is estimated and a regression model is fitted that includes the spline of the estimated logit propensity score as a covariate. The predicted unconditional mean of the missing variable has a double robustness (DR) property under misspecification of the imputation model. We show that a simplified version of PSPP, which does not center other regressors prior to including them in the prediction model, also has the DR property. We also propose two extensions of PSPP, namely, stratified PSPP and bivariate PSPP, that extend the DR property to inferences about conditional means. These extended PSPP methods are compared with the PSPP method and simple alternatives in a simulation study and applied to an online weight loss study conducted by Kaiser Permanente.en_US
dc.format.extent150582 bytes
dc.format.extent3110 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherBlackwell Publishing Incen_US
dc.rights©2009 International Biometric Societyen_US
dc.subject.otherMissing at Randomen_US
dc.subject.otherPenalized Splineen_US
dc.subject.otherPropensityen_US
dc.titleExtensions of the Penalized Spline of Propensity Prediction Method of Imputationen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, Michigan 48109, U.S.A. email: rlittle@umich.eduen_US
dc.identifier.pmid19053998en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/65192/1/j.1541-0420.2008.01155.x.pdf
dc.identifier.doi10.1111/j.1541-0420.2008.01155.xen_US
dc.identifier.sourceBiometricsen_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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