Statistical analysis with measurement error or misclassification strategy, method and application PDF
Preview Statistical analysis with measurement error or misclassification strategy, method and application
Springer Series in Statistics Grace Y. Yi Statistical Analysis with Measurement Error or Misclassifi cation Strategy, Method and Application Springer Series in Statistics Advisors: P.Bickel,P.Diggle,S.E.Feinberg,U.Gather, S.Zeger Moreinformationaboutthisseriesathttp://www.springer.com/series/692 Grace Y. Yi Statistical Analysis with Measurement Error or Misclassification Strategy, Method and Application 123 GraceY.Yi DepartmentofStatisticsandActuarialScience UniversityofWaterloo Waterloo,Canada ISSN0172-7397 ISSN2197-568X (electronic) SpringerSeriesinStatistics ISBN978-1-4939-6638-7 ISBN978-1-4939-6640-0 (eBook) DOI10.1007/978-1-4939-6640-0 LibraryofCongressControlNumber:2016951935 ©SpringerScience+BusinessMedia,LLC2017 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped. 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Tomyhusband,Wenqing,mychildren,MorganandJoy, andmyparents,LiangyuandZhizhen Foreword This book is an authoritative addition to the literature on measurement error and misclassification.Iliketothinkofthefieldmorebroadlyasstatisticalanalysiswhen variablesaresubjecttouncertaintyofmeasurement,althoughthecontextofmeasure- menterrorandmisclassificationisdifferentfromthecontextofuncertaintyquantifi- cationinappliedmathematicsandcomputermodeling. This book differs considerably from previous books by Fuller (1987), Carroll et al. (1995, 2006), Gustafson (2004), and Buonaccorsi (2010) because of its com- prehensiveoverviewoftopicsinlifetimedataanalysis,oftencalledsurvivalanalysis. If they touch at all on this important topic, which has quite a large literature, they touch it only very lightly. Grace Yi’s book covers proportional hazard/Cox regres- sion,additivehazardsurvivalmodels,andrecurrenteventdataandisthefirsttextto covertheseimportanttopicsindetail.Ofcourse,thefactthattheauthorisanexpert onthesetopicsisveryimportant,andanyonewantingtoknowaboutuncertaintyof measurementinlifetimedataanalysiswillwantthistextastheirguide. Threeotherchaptersarealsounique:(a)longitudinaldataanalysis,(b)multistate and Markov models, and (c) case–control studies. Again, these topics are touched upononlylightlybytheotherbooks,butGraceYihasgivenusaterrificoverviewof theliterature,onenotavailableelsewhere.Ihappentoknowquitealotaboutcase– controlandotherretrospective studies,andIamimpressedbythebook’s coverage ofthearea,andtheimportantwarningsthatgowiththisformofsampling. Not only are new topics covered in this book, but in addition they are covered extremelywell.Notjustauthoritatively,butalsoGraceYihasmadegreateffortsto communicatetheimportantideaswell.Thebookcanbeusedinteachingcourses,at VII VIII Foreword all levels ranging all the way up to advanced seminars. I though treasure the book becauseIknowthatIhavearesourceforunderstandingissuesinlifetimedataanal- ysis,notanareaIamcomfortablewith,butoneIconfrontonaregularbasis. DepartmentofStatistics RaymondJ.Carroll TexasA&MUniversity CollegeStation,TX77843-3143,USA and SchoolofMathematicalandPhysicalSciences UniversityofTechnologySydney Broadway,NSW2007,Australia Preface Measurement error and misclassification arise ubiquitously and have been a long- standing concern in statistical analysis. The effects of measurement error and mis- classificationhavebeenwelldocumentedformanysettingssuchaslinearregression and nonlinear regression models. Consequences of ignoring measurement error or misclassificationvaryfromproblemtoproblem;sometimestheeffectsarenegligible whileothertimestheycanbedrastic.Ageneralconsensusistoconductacase-by- caseexaminationinordertoreachavalidstatisticalanalysisforerror-contaminated data. Overthepastfewdecades,extensiveresearchhasbeendirectedtovariousfields concerning suchproblems.Researchinterestinmeasurementerrorandmisclassifi- cationproblemshasbeenrapidlyspurredinawidespectrumofdata,includingevent historydata(suchassurvivaldataandrecurrenteventdata),correlateddata(suchas longitudinal data and clustered data), multi-state event data, and data arising from case–control studies. The literature on this topic is enormous with many methods scattered diversely. The goal of this monograph is to bring together assorted meth- ods under the same umbrella and to provide an update on the recent development for a variety of settings. Measurement error effects and strategies of handling mis- measurement for different models are to be closely examined in combination with applicationstospecificproblems. A number of books concerning measurement error and misclassification have been published with distinct focuses. An early book by Fuller (1987) summarizes the development of linear regression models with errors-in-variables. Focusing on nonlinear measurement error models, Carroll, Ruppert and Stefanski (1995) pro- vide analysis strategies for regression problems in which covariates are measured with error; the second edition, Carroll et al. (2006), further documents up-to-date methods with a comprehensive discussion on many topics on nonlinear measure- menterrormodels,includingBayesiananalysismethods.Withtheemphasisonthe use of relatively simple methods, Buonaccorsi (2010) describes methods to correct IX X Preface formeasurementerrorandmisclassificationeffectsforregressionmodels.Underthe Bayesianparadigm,Gustafson(2004)providesadualtreatmentofmismeasurement in both continuous and categorical variables. Other relevant books on this topic include Biemer et al. (1991), Cheng and Van Ness (1999), Wansbeek and Meijer (2000),andDunn(2004). This monograph covers the material that complements those books, although there is overlap in some of the topics. While general principles and strategies may share certain similarities, this book emphasizes unique features in modeling and analyzing measurement error and misclassification problems arising from medical researchandepidemiologicalstudies.Theemphasisisongaininginsightintoprob- lemscomingfromawiderangeoffields.Thisbookaimstopresentbothstatistical theory and applications in a self-contained and coherent manner. To increase read- abilityandeasetheaccessforthereaders,necessarybackgroundandbasicinference frameworksforerror-freecontextsarepresentedatthebeginningofChapters3–8,in additiontothediscussioninChapter1.Eachchapterisconcludedwithbibliographic notesanddiscussion,supplementedwithexerciseproblemswhichmaybeusedfor graduatecourseteaching.Extensivereferencestorecentdevelopment aregivenfor thereadersinterestedinresearchonvariousmeasurementerrorandmisclassification problems.Applicationsandnumericalillustrationsaresupplied. This monograph is designed for multiple purposes. It can serve as a reference bookforresearcherswhoareinterestedinstatisticalmethodologyforhandlingdata withmeasurementerrorormisclassification.Itmaybeusedasatextbookforgrad- uatestudents,especiallyforthosemajoringinStatisticsandBiostatistics.Thisbook mayalsobeusedbyappliedstatisticianswhoseinterestfocusesonanalysisoferror- contaminateddata. This monograph is intended to be read by readers with diverse backgrounds. Familiaritywithinferencemethods(suchaslikelihoodandestimatingfunctionthe- ory)ormodelingschemesinvaryingsettings(suchassurvivalanalysisandlongitu- dinaldataanalysis)canresultinafullappreciationofthetext,butthisisnotessential. Readerswhoarenotfamiliarwiththosetopicsmayenjoyreadingthebookbygoing throughrelevanttopics.Chapters1–2andthefirstsectionofeachfollowingchapter provide basic inference frameworks and background material which are useful for unfamiliarreaders.Thebookdoesnothavetobereadaccordingtothesequentialor- derofthechapters.Readersmaydirectlyreadachapterofinterestbyskippingprior chapters.Theexercisesattheendofeachchaptersupplementthedevelopmentinthe text.Someproblemsareorganizedtoprovidejustificationoftheresultsdiscussedin thetext;someproblemsaremodifiedfromresearchpapersormonographstoserveas applicationsofthemethodsdiscussedinthetext;andsomeproblemsaredesignedto bepotentialresearchtopicswhichareworthfurtherexplorations.Referencesatthe endoftheproblemsindicatethesourcesfromwhichtheproblemsaremodified.
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