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DetailsFrom the EPOCE estimates and the individual contributions to the prognostic observed log-likelihood obtained with Delta(MPOL) +/- qnorm(0.975)*sqrt(VARIANCE) for an external dataset Delta(CVPOL) +/- qnorm(0.975)*sqrt(VARIANCE) for the dataset used in where Delta(CVPOL) (or Delta(MPOL)) is the difference of CVPOL (or MPOL) of the two joint latent class models, and VARIANCE is the empirical variance of the difference of individual contributions to the prognostic observed log-likelihoods of the two joint latent class models. See Commenges et al. (2012) and Proust-Lima et al. (2012) for further details. Value
Author(s)Cecile Proust-Lima and Amadou Diakite ReferencesCommenges, Liquet and Proust-Lima (2012). Choice of prognostic estimators in joint models by estimating differences of expected conditional Kullback-Leibler risks. Biometrics 68(2), 380-7. Proust-Lima, Sene, Taylor, Jacqmin-Gadda (2014). Joint latent class models for longitudinal and time-to-event data: a review. Statistical Methods in Medical Research 23, 74-90. See Also
Examples## Not run: #### estimation with 2 latent classes (ng=2) m2 <- Jointlcmm(fixed= Ydep1~Time*X1,random=~Time,mixture=~Time,subject='ID' ,survival = Surv(Tevent,Event)~ X1+X2 ,hazard="Weibull" ,hazardtype="PH",ng=2,data=data_lcmm, B=c( 0.7608, -9.4974, 1.0242, 1.4331, 0.1063 , 0.6714, 10.4679, 11.3178, -2.5671, -0.5386, 1.4616, -0.0605, 0.9489, 0.1020, 0.2079, 1.5045),logscale=TRUE) m1 <- Jointlcmm(fixed= Ydep1~Time*X1,random=~Time,subject='ID' ,survival = Surv(Tevent,Event)~ X1+X2 ,hazard="Weibull" ,hazardtype="PH",ng=1,data=data_lcmm, B=c(-7.6634, 0.9136, 0.1002, 0.6641, 10.5675, -1.6589, 1.4767, -0.0806, 0.9240,0.5643, 1.2277, 1.5004)) ## EPOCE computation for predictions times from 1 to 6 on the dataset used ## for estimation of m. VecTime <- c(1,3,5,7,9,11,13,15) cvpol1 <- epoce(m1,var.time="Time",pred.times=VecTime) cvpol1 cvpol2 <- epoce(m2,var.time="Time",pred.times=VecTime) cvpol2 DeltaEPOCE <- Diffepoce(cvpol1,cvpol2) summary(DeltaEPOCE) plot(DeltaEPOCE,bty="l") ## End(Not run) Results |
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