90 lines
3.1 KiB
Plaintext
90 lines
3.1 KiB
Plaintext
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R Under development (unstable) (2022-07-22 r82614) -- "Unsuffered Consequences"
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Copyright (C) 2022 The R Foundation for Statistical Computing
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Platform: x86_64-pc-linux-gnu (64-bit)
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R is free software and comes with ABSOLUTELY NO WARRANTY.
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You are welcome to redistribute it under certain conditions.
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Type 'license()' or 'licence()' for distribution details.
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R is a collaborative project with many contributors.
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Type 'contributors()' for more information and
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'citation()' on how to cite R or R packages in publications.
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Type 'demo()' for some demos, 'help()' for on-line help, or
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'help.start()' for an HTML browser interface to help.
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Type 'q()' to quit 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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> #
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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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>
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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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>
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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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>
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> temp <- c('coefficients', 'var', 'loglik', 'linear.predictors',
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+ 'means', 'n', 'concordance')
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>
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> all.equal(tfit1[temp], tfit2[temp])
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[1] TRUE
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> all.equal(tfit2[temp], tfit3[temp])
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[1] TRUE
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>
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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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[1] TRUE
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>
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>
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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$x2 <- rep(1:2, rep(nrow(test1),2))
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> zz <- zz2 <- rep(0, nrow(test3))
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> tfit1 <- coxph(Surv(time,status) ~x + strata(x2), test3, eps=1e-7)
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> tfit2 <- coxph(Surv(time,status) ~x + frailty(zz, theta=0, sparse=T)
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+ + strata(x2), test3)
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> tfit3 <- coxph(Surv(zz,time,status) ~x + frailty(zz2, theta=0, sparse=T)
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+ + strata(x2), test3)
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>
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> all.equal(tfit1[temp], tfit2[temp])
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[1] TRUE
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> all.equal(tfit2[temp], tfit3[temp])
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[1] TRUE
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>
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>
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> test4 <- rbind(test2, test2)
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> test4$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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[1] TRUE
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>
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> rm(test3, test4, tfit1, tfit2, tfit3, temp, zz, zz2)
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>
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> proc.time()
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user system elapsed
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1.002 0.057 1.051
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