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1、CHAPTER4MixedEffectsModelswithMissingData4.1IntroductionInChapter3,wehavereviewedsomecommonlyusedmethodsforgeneralmissingdataproblems.Missingdatamethodsforregressionmodelsarere-viewedinLittleandRubin(2002),Ibrahimetal.(2005),andMolenberghsandKenward(2007),amongothers
2、.Thesereviewsmostlyfocusonmodelsforcross-sectionaldata.Inpractice,missingdataareespeciallycommoninlongi-tudinalstudies.Inthischapter,wedescribesomestatisticalmethodsforvariousmissingdataproblemsinmixedeffectsmodels,includingLME,GLMM,andNLMEmodels.Wewilldiscussmissing
3、datainsurvivalmodelsandfrailtymodelsinChapter7.Weconsiderthefollowingmissingdataproblemsinmixedeffectsmodels:missingcovariates,missingresponses,missingbothcovariatesandresponses,dropouts.Anadvantageofthelikelihoodmethodformixedeffectsmodelsisthatital-lowsunbalanc
4、eddataintheresponse,i.e.,thenumbersandschedulesoftheresponsemeasurementscanbedifferentacrossindividuals.Inotherwords,iftherearemissingdataintheresponseandthemissingdatamechanismisig-norable(e.g.,MARorMCAR),wecansimplyignorethesemissingresponsesandproceedwithlikelihoo
5、dinference.Ifthemissingdataintheresponseofamixedeffectsmodelarenon-ignorable,however,wemustassumeamissingdatamodelandincorporateitinlikelihoodinference.Missingdatamayalsooccurincovariates.Therearetwotypesofcovariatesinlongitudinalstudies:time-independentcovariatesand
6、time-dependentco-131132MIXEDEFFECTSMODELSFORCOMPLEXDATAvariates.Time-independentcovariatesareonlymeasuredonceinalongitudi-nalstudyortheirvaluesdonotchangeovertime,suchasbaselinecovariatesorgenderandrace.Time-dependentcovariatesaremeasuredrepeatedlyovertimeortheirvalu
7、eschangeovertime.Foramixedeffectsmodelwithtime-dependentcovariates,standardmodelspecicationsrequirethatallcovariatevaluesareavailableatthesametimesastheresponsemeasurements.How-ever,thisisoftennotthecaseinpracticesincesomecovariatevaluesmaynotbeavailableattherespons
8、emeasurementtimes.Thisleadstomissingdataintime-dependentcovariates,whichisaverycommonproblem.Time-independentcovariatesmayalsohavem