Transcription of 237-2009: Analysis of Survival Data with Clustered ... - SAS
{{id}} {{{paragraph}}}
Example: tourism industry
237-2009: Analysis of Survival Data with Clustered ... - SAS
1 Paper 237-2009 Analysis of Survival Data with Clustered EventsLida Gharibvand, University of California, RiversideLei Liu, University of Virginia, CharlottesvilleABSTRACTTwo methods to analyzing Survival data with Clustered events are presented. The first method is a proportional hazards model which adopts a marginal approach with a working independence assumption. This model can be fitted by SAS PROC PHREG with the robust sandwich estimate option. The second method is a likelihood-based random effects (frailty) model. In the second model, the baseline hazard could be either a priori determined ( , Weibull) or approximated by piecewise constant counterpart. The estimation could be carried out by adaptive Gaussian quadrature method which is implemented in SAS PROC NLMIXED.
3 j =1,2, . . . ,J members. We record the follow-up time Xij for each member, which is the minimum of the failure time Dij and the non-informative censoring timeCij.Denote by ij I(Dij Cij) the event indicator, where I(.) is the indicator function.For each member there is a covariate vector Zij (t) for fixed effects at time t. The marginal Cox model for the jth event and the ith cluster is given by
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: