%load_ext rpy2.ipython
We mustn't be afraid to dream a little bigger :)
%%R
library(survival)
addicts <- read.csv("demo_surv/addicts.csv", head=TRUE)
Y <- with(addicts, Surv(survtime, status == 1))
model_coxph <- coxph(Y ~ strata(clinic) + prison + mdosedata, data=addicts)
print(summary(model_coxph))
Loading required package: splines Call: coxph(formula = Y ~ strata(clinic) + prison + mdosedata, data = addicts) n= 238, number of events= 150 coef exp(coef) se(coef) z Pr(>|z|) prison 0.3690 1.4463 0.1685 2.191 0.0285 * mdosedata -0.4349 0.6473 0.1031 -4.218 2.46e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 exp(coef) exp(-coef) lower .95 upper .95 prison 1.4463 0.6914 1.0396 2.0121 mdosedata 0.6473 1.5449 0.5289 0.7923 Concordance= 0.628 (se = 0.033 ) Rsquare= 0.087 (max possible= 0.994 ) Likelihood ratio test= 21.54 on 2 df, p=2.103e-05 Wald test = 21.53 on 2 df, p=2.108e-05 Score (logrank) test = 22.11 on 2 df, p=1.583e-05 NULL
%%R
library(ggplot2)
library(data.table)
source('demo_surv/myggsurv.R')
model_clinic <- with(addicts, Surv(survtime, status==1) ~ clinic)
g_dose <- myggsurv(
survfit(model_clinic),
xlab='Time stay in the experiement (days)', ylab='Survival probability'
) + theme_classic(18)
g <- g_dose + theme(legend.position=c(0, 0), legend.justification=c(0, 0)) +
labs(title='KM curves', color='Categories') +
scale_color_brewer(palette='Paired')
show(g)
data.table 1.9.2 For help type: help("data.table") Scale for 'colour' is already present. Adding another scale for 'colour', which will replace the existing scale. NULL