Multistate event history analysis with frailty

TY - JOUR

T1 - Multistate event history analysis with frailty

AU - Bijwaard, G.E.

N1 - Reporting year: 2014

PY - 2014

Y1 - 2014

N2 - BACKGROUND In survival analysis a large literature using frailty models, or models with unobserved heterogeneity, exists. In the growing literature and modelling on multistate models, this issue is only in its infant phase. Ignoring frailty can, however, produce incorrect results.OBJECTIVE This paper presents how frailties can be incorporated into multistate models, with an emphasis on semi-Markov multistate models with a mixed proportional hazard structure.METHODS First, the aspects of frailty modeling in univariate (proportional hazard, Cox) and multivariate event history models are addressed. The implications of choosing shared or correlated frailty is highlighted. The relevant differences with recurrent events data are covered next. Multistate models are event history models that can have both multivariate and recurrent events. Incorporating frailty in multistate models, therefore, brings all the previously addressed issues together. Assuming a discrete frailty distribution allows fora very general correlation structure among the transition hazards in a multistate model.Although some estimation procedures are covered the emphasis is on conceptual issues.RESULTS The importance of multistate frailty modeling is illustrated with data on labour market and migration dynamics of recent immigrants to the Netherlands.

AB - BACKGROUND In survival analysis a large literature using frailty models, or models with unobserved heterogeneity, exists. In the growing literature and modelling on multistate models, this issue is only in its infant phase. Ignoring frailty can, however, produce incorrect results.OBJECTIVE This paper presents how frailties can be incorporated into multistate models, with an emphasis on semi-Markov multistate models with a mixed proportional hazard structure.METHODS First, the aspects of frailty modeling in univariate (proportional hazard, Cox) and multivariate event history models are addressed. The implications of choosing shared or correlated frailty is highlighted. The relevant differences with recurrent events data are covered next. Multistate models are event history models that can have both multivariate and recurrent events. Incorporating frailty in multistate models, therefore, brings all the previously addressed issues together. Assuming a discrete frailty distribution allows fora very general correlation structure among the transition hazards in a multistate model.Although some estimation procedures are covered the emphasis is on conceptual issues.RESULTS The importance of multistate frailty modeling is illustrated with data on labour market and migration dynamics of recent immigrants to the Netherlands.

KW - SSCI

U2 - 10.4054/DemRes.2014.30.58

DO - 10.4054/DemRes.2014.30.58

M3 - Article

SN - 1435-9871

VL - 30

SP - 1591

EP - 1620

JO - Demographic Research

JF - Demographic Research

M1 - 58

ER -