98 lines
3.0 KiB
Plaintext
98 lines
3.0 KiB
Plaintext
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R Under development (unstable) (2021-02-16 r80015) -- "Unsuffered Consequences"
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Copyright (C) 2021 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 some more features of surv.diff
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> #
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> # First, what happens when one group is a dummy
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> #
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>
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>
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> #
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> # The AML data, with a third group of early censorings "tacked on"
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> #
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> aml3 <- list(time= c( 9, 13, 13, 18, 23, 28, 31, 34, 45, 48, 161,
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+ 5, 5, 8, 8, 12, 16, 23, 27, 30, 33, 43, 45,
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+ 1, 2, 2, 3, 3, 3, 4),
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+ status= c( 1,1,0,1,1,0,1,1,0,1,0, 1,1,1,1,1,0,1,1,1,1,1,1,
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+ 0,0,0,0,0,0,0),
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+ x = as.factor(c(rep("Maintained", 11),
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+ rep("Nonmaintained", 12), rep("Dummy",7) )))
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>
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> aml3 <- data.frame(aml3)
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>
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> # These should give the same result (chisq, df), but the second has an
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> # extra group
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> survdiff(Surv(time, status) ~x, aml)
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Call:
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survdiff(formula = Surv(time, status) ~ x, data = aml)
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N Observed Expected (O-E)^2/E (O-E)^2/V
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x=Maintained 11 7 10.69 1.27 3.4
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x=Nonmaintained 12 11 7.31 1.86 3.4
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Chisq= 3.4 on 1 degrees of freedom, p= 0.07
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> survdiff(Surv(time, status) ~x, aml3)
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Call:
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survdiff(formula = Surv(time, status) ~ x, data = aml3)
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N Observed Expected (O-E)^2/E (O-E)^2/V
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x=Dummy 7 0 0.00 NaN NaN
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x=Maintained 11 7 10.69 1.27 3.4
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x=Nonmaintained 12 11 7.31 1.86 3.4
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Chisq= 3.4 on 1 degrees of freedom, p= 0.07
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>
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>
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> #
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> # Now a test of the stratified log-rank
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> # There are no tied times within institution, so the coxph program
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> # can be used to give a complete test
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> #
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> fit <- survdiff(Surv(time, status) ~ pat.karno + strata(inst), lung)
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>
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> cfit <- coxph(Surv(time, status) ~ factor(pat.karno) + strata(inst),
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+ lung, iter=0)
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>
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> tdata <- na.omit(lung[,c('time', 'status', 'pat.karno', 'inst')])
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>
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> temp1 <- tapply(tdata$status-1, list(tdata$pat.karno, tdata$inst), sum)
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> temp1 <- ifelse(is.na(temp1), 0, temp1)
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> temp2 <- tapply(cfit$resid, list(tdata$pat.karno, tdata$inst), sum)
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> temp2 <- ifelse(is.na(temp2), 0, temp2)
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>
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> temp2 <- temp1 - temp2
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>
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> #Now temp1=observed, temp2=expected
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> all.equal(c(temp1), c(fit$obs))
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[1] TRUE
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> all.equal(c(temp2), c(fit$exp))
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[1] TRUE
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>
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> all.equal(fit$var[-1,-1], solve(cfit$var))
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[1] TRUE
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>
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> rm(tdata, temp1, temp2)
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>
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> proc.time()
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user system elapsed
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0.827 0.047 0.867
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