114 lines
3.9 KiB
Plaintext
114 lines
3.9 KiB
Plaintext
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R Under development (unstable) (2018-01-04 r74052) -- "Unsuffered Consequences"
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Copyright (C) 2018 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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> # The Stanford data from 1980 is used in Escobar and Meeker, Biometrics 1992.
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> # t5 = T5 mismatch score
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> # Their case numbers correspond to a data set sorted by age
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> #
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> aeq <- function(x,y, ...) all.equal(as.vector(x), as.vector(y), ...)
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>
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> stanford2$t5 <- ifelse(stanford2$t5 <0, NA, stanford2$t5)
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> stanford2 <- stanford2[order(stanford2$age, stanford2$time),]
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> stanford2$time <- ifelse(stanford2$time==0, .5, stanford2$time)
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>
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> cage <- stanford2$age - mean(stanford2$age)
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> fit1 <- survreg(Surv(time, status) ~ cage + I(cage^2), stanford2,
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+ dist='lognormal')
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> fit1
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Call:
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survreg(formula = Surv(time, status) ~ cage + I(cage^2), data = stanford2,
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dist = "lognormal")
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Coefficients:
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(Intercept) cage I(cage^2)
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6.717591081 -0.061908619 -0.003504315
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Scale= 2.362872
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Loglik(model)= -863.6 Loglik(intercept only)= -868.8
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Chisq= 10.5 on 2 degrees of freedom, p= 0.00526
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n= 184
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> ldcase <- resid(fit1, type='ldcase')
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> ldresp <- resid(fit1, type='ldresp')
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> # The ldcase and ldresp should be compared to table 1 in Escobar and
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> # Meeker, Biometrics 1992, p519; the colums they label as (1/2) A_{ii}
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> # They give data for selected cases, entered below as mdata
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> mdata <- cbind(c(1,2,4,5,12,16,23,61,66,72,172,182,183,184),
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+ c(.035, .244, .141, .159, .194, .402, 0,0, .143, .403,
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+ .178, .033, .005, .015),
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+ c(.138, .145, .073, .076, .104, .159, 0,0, .109, .184,
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+ .116, .063, .103, .144))
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> dimnames(mdata) <- list(NULL, c("case#", "ldcase", "ldresp"))
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> aeq(round(ldcase[mdata[,1]],3), mdata[,2])
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[1] TRUE
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> aeq(round(ldresp[mdata[,1]],3), mdata[,3])
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[1] TRUE
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>
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> plot1 <- function() {
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+ # make their figure 1, 2, and 6
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+ temp <- predict(fit1, type='quantile', p=c(.1, .5, .9))
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+ plot(stanford2$age, stanford2$time, log='y', xlab="Age", ylab="Days",
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+ ylim=range(stanford2$time, temp))
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+ matlines(stanford2$age, temp, lty=c(1,2,2), col=1)
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+
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+ n <- length(ldcase)
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+ plot(1:n, ldcase, xlab="Case Number", ylab="(1/2) A", type='l')
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+ title (main="Case weight pertubations")
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+ plot(1:n, ldresp, xlab="Case Number", ylab="(1/2) A",
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+ ylim=c(0, .2), type='l')
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+ title(main="Response pertubations")
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+ indx <- which(ldresp > .07)
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+ text(indx, ldresp[indx]+ .005, indx%%10, cex=.6)
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+ }
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>
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> postscript('meekerplot.ps')
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> plot1()
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> dev.off()
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null device
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1
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> #
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> # Stanford predictions in other ways
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> #
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> fit2 <- survreg(Surv(time, status) ~ poly(age,2), stanford2,
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+ dist='lognormal')
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>
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> p1 <- predict(fit1, type='response')
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> p2 <- predict(fit2, type='response')
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> aeq(p1, p2)
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[1] TRUE
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>
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> p3 <- predict(fit2, type='terms', se=T)
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> p4 <- predict(fit2, type='lp', se=T)
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> p5 <- predict(fit1, type='lp', se=T)
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> # aeq(p3$fit + attr(p3$fit, 'constant'), p4$fit) #R is missing the attribute
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> aeq(p4$fit, p5$fit)
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[1] TRUE
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> aeq(p3$se.fit, p4$se.fit) #this one should be false
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[1] "Mean relative difference: 0.758395"
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> aeq(p4$se.fit, p5$se.fit) #this one true
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[1] TRUE
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>
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>
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> proc.time()
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user system elapsed
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0.864 0.064 0.925
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