165 lines
5.7 KiB
R
165 lines
5.7 KiB
R
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### R code from vignette source 'splines.Rnw'
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###################################################
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### code chunk number 1: splines.Rnw:21-25
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###################################################
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options(continue=" ", width=60)
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options(SweaveHooks=list(fig=function() par(mar=c(4.1, 4.1, .3, 1.1))))
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pdf.options(pointsize=8) #text in graph about the same as regular text
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options(contrasts=c("contr.treatment", "contr.poly")) #reset default
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###################################################
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### code chunk number 2: mplot
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###################################################
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getOption("SweaveHooks")[["fig"]]()
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library(survival)
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mfit <- coxph(Surv(futime, death) ~ sex + pspline(age, df=4), data=mgus)
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mfit
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termplot(mfit, term=2, se=TRUE, col.term=1, col.se=1)
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###################################################
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### code chunk number 3: mplot2
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###################################################
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ptemp <- termplot(mfit, se=TRUE, plot=FALSE)
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attributes(ptemp)
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ptemp$age[1:4,]
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###################################################
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### code chunk number 4: mplot3
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###################################################
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getOption("SweaveHooks")[["fig"]]()
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ageterm <- ptemp$age # this will be a data frame
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center <- with(ageterm, y[x==50])
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ytemp <- ageterm$y + outer(ageterm$se, c(0, -1.96, 1.96), '*')
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matplot(ageterm$x, exp(ytemp - center), log='y',
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type='l', lty=c(1,2,2), col=1,
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xlab="Age at diagnosis", ylab="Relative death rate")
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###################################################
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### code chunk number 5: hgb
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###################################################
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getOption("SweaveHooks")[["fig"]]()
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fit <- coxph(Surv(futime, death) ~ age + pspline(hgb, 4), mgus2)
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fit
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termplot(fit, se=TRUE, term=2, col.term=1, col.se=1,
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xlab="Hemoglobin level")
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###################################################
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### code chunk number 6: df
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###################################################
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getOption("SweaveHooks")[["fig"]]()
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termplot(fit, se=TRUE, col.term=1, col.se=1, term=2,
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xlab="Hemoglobin level", ylim=c(-.4, 1.3))
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df <- c(3, 2.5, 2)
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for (i in 1:3) {
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tfit <- coxph(Surv(futime, death) ~ age +
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pspline(hgb, df[i], nterm=8), mgus2)
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temp <- termplot(tfit, se=FALSE, plot=FALSE, term=2)
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lines(temp$hgb$x, temp$hgb$y, col=i+1, lwd=2)
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}
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legend(14, 1, paste("df=", c(4, df)), lty=1, col=1:4, lwd=2)
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###################################################
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### code chunk number 7: fit2a
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###################################################
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getOption("SweaveHooks")[["fig"]]()
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fit2a <- coxph(Surv(futime, death) ~ age + pspline(hgb, 2.5, nterm=8), mgus2)
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coef(fit2a)
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plot(1:10, coef(fit2a)[-1])
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###################################################
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### code chunk number 8: fit2b
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###################################################
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getOption("SweaveHooks")[["fig"]]()
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temp <- c(1:7, 8,8,8)
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fit2b <- coxph(Surv(futime, death) ~ age +
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pspline(hgb, 2.5, nterm=8, combine=temp),
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data= mgus2)
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temp2 <- c(1:6, 7,7,7,7)
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fit2c <- coxph(Surv(futime, death) ~ age +
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pspline(hgb, 2.5, nterm=8, combine=temp2),
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data= mgus2)
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matplot(1:10, cbind(coef(fit2a)[-1], coef(fit2b)[temp+1],
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coef(fit2c)[temp2+1]), type='b', pch='abc',
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xlab="Term", ylab="Pspline coef")
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###################################################
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### code chunk number 9: fit1
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###################################################
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getOption("SweaveHooks")[["fig"]]()
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options(show.signif.stars=FALSE) # display intelligence
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fit1 <- coxph(Surv(futime, death) ~ sex + pspline(age, 3), data=flchain)
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fit1
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termplot(fit1, term=2, se=TRUE, col.term=1, col.se=1,
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ylab="log hazard ratio")
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###################################################
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### code chunk number 10: nfit
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###################################################
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options(show.signif.stars=FALSE) # display statistical intellegence
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require(splines, quietly=TRUE)
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nfit1 <- coxph(Surv(futime, death) ~ sex + age, flchain)
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nfit2 <- coxph(Surv(futime, death) ~ sex + ns(age, df=3), flchain)
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nfit3 <- coxph(Surv(futime, death) ~ sex * ns(age, df=3), flchain)
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anova(nfit1, nfit2, nfit3)
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###################################################
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### code chunk number 11: nfit2
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###################################################
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getOption("SweaveHooks")[["fig"]]()
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pdata <- expand.grid(age= 50:99, sex=c("F", "M"))
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pdata[1:5,]
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ypred <- predict(nfit3, newdata=pdata, se=TRUE)
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yy <- ypred$fit + outer(ypred$se, c(0, -1.96, 1.96), '*')
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matplot(50:99, exp(matrix(yy, ncol=6)), type='l', lty=c(1,1,2,2,2,2),
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lwd=2, col=1:2, log='y',
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xlab="Age", ylab="Relative risk")
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legend(55, 20, c("Female", "Male"), lty=1, lwd=2, col=1:2, bty='n')
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abline(h=1)
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###################################################
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### code chunk number 12: fit2
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###################################################
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agem <- with(flchain, ifelse(sex=="M", age, 60))
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agef <- with(flchain, ifelse(sex=="F", age, 60))
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fit2 <- coxph(Surv(futime, death) ~ sex + pspline(agef, df=3)
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+ pspline(agem, df=3), data=flchain)
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anova(fit2, fit1)
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###################################################
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### code chunk number 13: plot2
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###################################################
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getOption("SweaveHooks")[["fig"]]()
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# predictions
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pdata2 <- pdata
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pdata2$agem <- with(pdata2, ifelse(sex=="M", age, 60))
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pdata2$agef <- with(pdata2, ifelse(sex=="F", age, 60))
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ypred2 <- predict(fit2, pdata2, se=TRUE)
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yy <- ypred2$fit + outer(ypred2$se, c(0, -1.96, 1.96), '*')
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# reference
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refdata <- data.frame(sex='F', agef=65, agem=60)
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ref <- predict(fit2, newdata=refdata, type="lp")
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# plot
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matplot(50:99, exp(matrix(yy-ref, ncol=6)), type='l', lty=c(1,1,2,2,2,2),
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lwd=2, col=1:2, log='y',
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xlab="Age", ylab="Relative risk")
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legend(55, 20, c("Female", "Male"), lty=1, lwd=2, col=1:2, bty='n')
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abline(h=1)
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