
R version 3.4.1 (2017-06-30) -- "Single Candle"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> options(na.action=na.exclude) # preserve missings
> options(contrasts=c('contr.treatment', 'contr.poly')) #ensure constrast type
> library(survival)
> 
> aeq <- function(x,y, ...) all.equal(as.vector(x), as.vector(y), ...)
> 
> lfit2 <- survreg(Surv(time, status) ~ age + ph.ecog + strata(sex), lung)
> lfit3 <- survreg(Surv(time, status) ~ sex + (age+ph.ecog)*strata(sex), lung)
> 
> lfit4 <-  survreg(Surv(time, status) ~ age + ph.ecog , lung,
+ 		  subset=(sex==1))
> lfit5 <- survreg(Surv(time, status) ~ age + ph.ecog , lung,
+ 		  subset=(sex==2))
> 
> if (exists('censorReg')) {
+     lfit1 <- censorReg(censor(time, status) ~ age + ph.ecog + strata(sex),lung)
+     aeq(lfit4$coef, lfit1[[1]]$coef)
+     aeq(lfit4$scale, lfit1[[1]]$scale)
+     aeq(c(lfit4$scale, lfit5$scale), sapply(lfit1, function(x) x$scale))
+     }
> aeq(c(lfit4$scale, lfit5$scale), lfit3$scale )
[1] TRUE
> 
> #
> # Test out ridge regression and splines
> #
> lfit0 <- survreg(Surv(time, status) ~1, lung)
> lfit1 <- survreg(Surv(time, status) ~ age + ridge(ph.ecog, theta=5), lung)
> lfit2 <- survreg(Surv(time, status) ~ sex + ridge(age, ph.ecog, theta=1), lung)
> lfit3 <- survreg(Surv(time, status) ~ sex + age + ph.ecog, lung)
> 
> lfit0
Call:
survreg(formula = Surv(time, status) ~ 1, data = lung)

Coefficients:
(Intercept) 
   6.034904 

Scale= 0.7593936 

Loglik(model)= -1153.9   Loglik(intercept only)= -1153.9
n= 228 
> lfit1
Call:
survreg(formula = Surv(time, status) ~ age + ridge(ph.ecog, theta = 5), 
    data = lung)

               coef     se(coef) se2     Chisq DF p      
(Intercept)     6.83082 0.42860  0.42860 254.0 1  3.5e-57
age            -0.00783 0.00687  0.00687   1.3 1  2.5e-01
ridge(ph.ecog) -0.32032 0.08484  0.08405  14.2 1  1.6e-04

Scale= 0.738 

Iterations: 1 outer, 5 Newton-Raphson
Degrees of freedom for terms= 1 1 1 1 
Likelihood ratio test=18.6  on 2 df, p=9e-05
  n=227 (1 observation deleted due to missingness)
> lfit2
Call:
survreg(formula = Surv(time, status) ~ sex + ridge(age, ph.ecog, 
    theta = 1), data = lung)

               coef     se(coef) se2     Chisq  DF p      
(Intercept)     6.27163 0.45280  0.45210 191.84 1  1.3e-43
sex             0.40096 0.12371  0.12371  10.50 1  1.2e-03
ridge(age)     -0.00746 0.00675  0.00674   1.22 1  2.7e-01
ridge(ph.ecog) -0.33848 0.08329  0.08314  16.51 1  4.8e-05

Scale= 0.731 

Iterations: 1 outer, 6 Newton-Raphson
Degrees of freedom for terms= 1 1 2 1 
Likelihood ratio test=30  on 3 df, p=1e-06
  n=227 (1 observation deleted due to missingness)
> lfit3
Call:
survreg(formula = Surv(time, status) ~ sex + age + ph.ecog, data = lung)

Coefficients:
 (Intercept)          sex          age      ph.ecog 
 6.273435252  0.401090541 -0.007475439 -0.339638098 

Scale= 0.731109 

Loglik(model)= -1132.4   Loglik(intercept only)= -1147.4
	Chisq= 29.98 on 3 degrees of freedom, p= 1.39e-06 
n=227 (1 observation deleted due to missingness)
> 
> 
> xx <- pspline(lung$age, nterm=3, theta=.3)
> xx <- matrix(unclass(xx), ncol=ncol(xx))   # the raw matrix
> lfit4 <- survreg(Surv(time, status) ~xx, lung)
> lfit5 <- survreg(Surv(time, status) ~age, lung)
> 
> lfit6 <- survreg(Surv(time, status)~pspline(age, df=2), lung)
> 
> lfit7 <- survreg(Surv(time, status) ~ offset(lfit6$lin), lung)
> 
> lfit4
Call:
survreg(formula = Surv(time, status) ~ xx, data = lung)

Coefficients:
(Intercept)         xx1         xx2         xx3         xx4         xx5 
  13.551290   -7.615741   -7.424565   -7.533378   -7.571272  -14.527489 

Scale= 0.755741 

Loglik(model)= -1150.1   Loglik(intercept only)= -1153.9
	Chisq= 7.52 on 5 degrees of freedom, p= 0.185 
n= 228 
> lfit5
Call:
survreg(formula = Surv(time, status) ~ age, data = lung)

Coefficients:
(Intercept)         age 
 6.88712062 -0.01360829 

Scale= 0.7587515 

Loglik(model)= -1151.9   Loglik(intercept only)= -1153.9
	Chisq= 3.91 on 1 degrees of freedom, p= 0.0479 
n= 228 
> lfit6
Call:
survreg(formula = Surv(time, status) ~ pspline(age, df = 2), 
    data = lung)

                          coef    se(coef) se2     Chisq  DF   p      
(Intercept)                6.5918 0.63681  0.41853 107.15 1.00 4.1e-25
pspline(age, df = 2), lin -0.0136 0.00687  0.00687   3.94 1.00 4.7e-02
pspline(age, df = 2), non                            0.78 1.06 4.0e-01

Scale= 0.756 

Iterations: 4 outer, 12 Newton-Raphson
     Theta= 0.926 
Degrees of freedom for terms= 0.4 2.1 1.0 
Likelihood ratio test=5.2  on 1.5 df, p=0.04  n= 228 
> signif(lfit7$coef,6)
(Intercept) 
1.47899e-09 
> 
> proc.time()
   user  system elapsed 
  1.959   0.081   2.236 
