63 lines
2.2 KiB
R
63 lines
2.2 KiB
R
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options(na.action=na.exclude) # preserve missings
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options(contrasts=c('contr.treatment', 'contr.poly')) #ensure constrast type
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library(survival)
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#
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# Test the logic of the penalized code by fitting some no-frailty models
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# (theta=0). It should give exactly the same answers as 'ordinary' coxph.
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#
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test1 <- data.frame(time= c(4, 3,1,1,2,2,3),
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status=c(1,NA,1,0,1,1,0),
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x= c(0, 2,1,1,1,0,0))
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test2 <- data.frame(start=c(1, 2, 5, 2, 1, 7, 3, 4, 8, 8),
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stop =c(2, 3, 6, 7, 8, 9, 9, 9,14,17),
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event=c(1, 1, 1, 1, 1, 1, 1, 0, 0, 0),
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x =c(1, 0, 0, 1, 0, 1, 1, 1, 0, 0) )
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zz <- zz2 <- rep(0, nrow(test1))
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tfit1 <- coxph(Surv(time,status) ~x, test1, eps=1e-7)
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tfit2 <- coxph(Surv(time,status) ~x + frailty(zz, theta=0, sparse=T), test1)
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tfit3 <- coxph(Surv(zz,time,status) ~x + frailty(zz2, theta=0, sparse=T), test1)
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temp <- c('coefficients', 'var', 'loglik', 'linear.predictors',
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'means', 'n', 'concordance')
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all.equal(tfit1[temp], tfit2[temp])
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all.equal(tfit2[temp], tfit3[temp])
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zz <- rep(0, nrow(test2))
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tfit1 <- coxph(Surv(start, stop, event) ~x, test2, eps=1e-7)
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tfit2 <- coxph(Surv(start, stop, event) ~ x + frailty(zz, theta=0, sparse=T),
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test2)
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all.equal(tfit1[temp], tfit2[temp])
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#
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# Repeat the above tests, but with a strata added
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# Because the data set is simply doubled, the loglik will double,
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# beta is the same, variance is halved.
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#
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test3 <- rbind(test1, test1)
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test3$x2 <- rep(1:2, rep(nrow(test1),2))
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zz <- zz2 <- rep(0, nrow(test3))
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tfit1 <- coxph(Surv(time,status) ~x + strata(x2), test3, eps=1e-7)
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tfit2 <- coxph(Surv(time,status) ~x + frailty(zz, theta=0, sparse=T)
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+ strata(x2), test3)
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tfit3 <- coxph(Surv(zz,time,status) ~x + frailty(zz2, theta=0, sparse=T)
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+ strata(x2), test3)
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all.equal(tfit1[temp], tfit2[temp])
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all.equal(tfit2[temp], tfit3[temp])
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test4 <- rbind(test2, test2)
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test4$x2 <- rep(1:2, rep(nrow(test2),2))
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zz <- rep(0, nrow(test4))
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tfit1 <- coxph(Surv(start, stop, event) ~x, test4, eps=1e-7)
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tfit2 <- coxph(Surv(start, stop, event) ~ x + frailty(zz, theta=0, sparse=T),
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test4)
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all.equal(tfit1[temp], tfit2[temp])
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rm(test3, test4, tfit1, tfit2, tfit3, temp, zz, zz2)
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