Multistate Analysis of Life Histories with R

323 Pages·2014·26.887 MB·English

by  Frans Willekens (auth.)

UseR!
Frans Willekens
Multistate
Analysis of
Life Histories
with R
Use R!
SeriesEditors
RobertGentleman
KurtHornik
GiovanniParmigiani
More information about this series at
http://www.springer.com/series/6991
Frans Willekens
Multistate Analysis of Life
Histories with R
FransWillekens
MaxPlanckInstituteforDemographicResearch
Rostock
Germany
ISSN2197-5736 ISSN2197-5744(electronic)
ISBN978-3-319-08382-7 ISBN978-3-319-08383-4(eBook)
DOI10.1007/978-3-319-08383-4
SpringerChamHeidelbergNewYorkDordrechtLondon
LibraryofCongressControlNumber:2014950218
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Preface
Supposeyouareaskedtodescribeanindividual.Youprobablylistage,sex,marital
status, presence of children and number of children, main occupation, education
level,ethnicity,placeofresidence,placeofwork,mainsourceofincome,religious
denomination and some lifestyle features. You probably add years of major tran-
sitions:whenthepersongraduatedfromschool,gotmarried,enteredthecurrentjob
andmovedtothecurrentaddress.Ifthepersonhaschildren,youmayaddthename,
ageandsexofeachchild.Whenyouareaskedtodescribeapopulation,youmay
mentionsize,agestructure,distributionbylevelofeducation,employmentstatus,
marital status and health status. It describes the population at a point in time. If
askedtodescribepopulation change,youmaymentionchanges insizeanddistri-
bution. Population change is an outcome of changes in people’s lifestyle and life
course.Anageingpopulationisaresultofpeoplehavingfewerchildrenandliving
longer. A declining married proportion is an outcome of fewer people marrying,
postponementofmarriageandmarriagesbeinglessstable.Fewermarriagesmaybe
linkedtochangesinthemeaningoftheinstitutionofmarriage.Anincreaseinthe
proportionofunemploymentisanoutcomeofmorepeoplelosingtheirjoband/or
decreasedlikelihoodoffindingajobwhenunemployed,resultinginlongerunem-
ploymentspells.Thedescriptionofpopulationchangeintermsofchanginglivesis
referredtoasthebiographicalmethod.Themethodemphasizespersonalattributes,
lifeeventsandlifehistories.
Anindividualmaybecharacterizedbyasetofattributessuchasmaritalstatus,
employmentstatus,healthstatus,placeofresidenceandincomelevel.Ifattributes
arerepresentedbydiscretevariableswithfinitenumbersofcategories,acombina-
tionofcategoriesdefinesastateofexistenceandanindividualwithgivenvaluesof
attributes is said to occupy a state. Individuals with the same values of attributes
occupythesamestate.Thestatespaceisthesetofpossiblestates.Inpractice,one
or a few attributes are selected to define the state space. Which attributes are
selected depends on the research question. Other attributes that are relevant but
notofprimaryimportancearetreatedascovariates.
Aslifeunfolds,anindividualmovesbetweenstates.Thesequencesofstatesand
transitionsbetweenstatesdescribelifehistoriesorcareers.Employmenthistories,
v
vi Preface
maritalhistoriesandresidentialhistoriesareexamplesofcareers.Instudiesoflife
histories, two approaches are distinguished (Abbott 2001). The first views a life
pathasawholeandtriestofindtypicalpatterns.Theapproachisgenerallyknown
assequenceanalysis.Thesecondviewsalifehistoryasarealizationofastochastic
process and aims at the description, explanation and prediction of life histories.
Probabilitymodelsareusedtorepresentstochasticprocessesandtomodelthelife
historiesthattheygenerate.Thisbookisaboutthesecondapproach.Lifehistories
are viewed as realizations of continuous-time Markov processes that depend on
ratesoftransitionbetweenstates.Theratesareestimatedfromlongitudinaldata.
The multistate methods that are presented in this book are included in the
software package Biograph, a package in R that implements the biographical
method. The packages can be downloaded from the Comprehensive R Archive
Network(CRAN)(http://cran.r-project.org/).Biographretrievesusefulinformation
fromlifehistorydata.Itestimatestransitionratesandcomputesusefullifehistory
indicators. A particularly useful feature of Biograph is the set of utilities that
connect the package to R packages for multistate modeling including mstate,
msm,mvna,etm,Epi,andthepackageTraMineRforsequenceanalysis.Biograph
producesinputdataintherightformatandbasicRobjectsforthepackages.
Themotivationtowritethebookwastostimulatetheuseofmultistatemodeling
among social science students and researchers with basic knowledge of survival
analysis and event history analysis. The methods presented in the book are illus-
trated using two data sets. The first is a subsample of the German Life History
Survey. Blossfeld and Rohwer (2002) and Blossfeld et al. (2007) used the data to
illustratethestatisticalmodelingoftime-to-eventdata.Byusingthesamedataset,
the multistate analysis of life histories is presented as a logical extension of the
analysis of time-to-event data. At the end of the book, another data set is consid-
ered: the Netherlands Fertility and Family Survey of 1998. The data sets are
includedintheBiographpackage.
Thebookshouldappealtoanyoneinterestedinhowpopulationschangeandhow
the change is related to the lifestyle and life course of individuals. The changes
include today’s major societal challenges: ageing, population decline, migration
and integration, population diversity, population health, labour market dynamics
and the role of education and skills in the modern knowledge society. The book
should be of particular interest to demographers, epidemiologists and students of
population health, sociologists, criminologists, economists and historians. The
book is suitable as a textbook for graduate courses on event history analysis. It
mayalsobeusedasaself-studybookprovidedthereaderhasabasicknowledgeof
survivalanalysisandmultistatemodeling.TheRcodeusedonthebookisavailable
online.
The preparation of the book has been a long but exciting journey. Most of the
work was done while I was with the Netherlands Interdisciplinary Demographic
Institute(NIDI)inTheHague.ThebookwascompletedattheMaxPlanckInstitute
forDemographicResearchinRostock,Germany.IwouldliketothankHans-Peter
BlossfeldforallowingmetousethesubsampleoftheGermanLifeHistorySurvey
Preface vii
thatheusedinhisbookwithGo¨tzRohwer,TechniquesofEventHistoryModeling
(BlossfeldandRohwer2002).JamesRaymer,JuttaGampe,SabineZinnandArthur
Allignolprovidedusefulcommentsonthemanuscript.Iamgratefulfortheirhelp.
Rostock,Germany FransWillekens
May2014
ThiSisaFMBlankPage
Contents
1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2 LifeHistories:RealandSynthetic. . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 TransitionRates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3 TransitionProbabilitiesandStateOccupationProbabilities. . . . . . 28
2.4 ExpectedWaitingTimesandStateOccupationTimes. . . . . . . . . 40
2.5 SyntheticLifeHistories. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
2.6 Conclusion. . .. . . . . . . . . . . .. . . . . . . . . . . .. . . . . . . . . . . .. . 51
3 TheBiographObject. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.2 DescriptionofaBiographObject. . . . . . . . . . . . . . . . . . . . . . . . 54
3.3 HowtoCreateaBiographObject?. . . . . . . . . . . . . . . . . . . . . . . 57
3.4 DataRestructuring. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.5 OtherDataFormats. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.6 ANoteonDates. . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. 74
3.7 Conclusion. . .. . . . . . . . . . . .. . . . . . . . . . . .. . . . . . . . . . . .. . 78
4 ExploratoryDataAnalysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.2 TheMultistateSystemandItsMeasurement. . . . . . . . . . . . . . . . 82
4.3 EpisodesandTransitions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
4.4 StateandEventSequences:IndividualandAggregate. . . . . . . . . 91
4.5 StateOccupancies,TransitionsandStateOccupationTimes. . . . . 95
4.6 Covariates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
4.7 Conclusion. . .. . . . . . . . . . . .. . . . . . . . . . . .. . . . . . . . . . . .. . 106
5 VisualisationofLifeHistories. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.2 PointsofDeparture. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
5.3 BasicGraphicswithggplot2. . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
ix