intubate (version 1.0.0)

survival: Interfaces to survival package for data science pipelines.

Description

Interfaces to survival functions that can be used in a pipeline implemented by magrittr.

Usage

ntbt_cch(data, ...)
ntbt_coxph(data, ...)
ntbt_pyears(data, ...)
ntbt_survConcordance(data, ...)
ntbt_survexp(data, ...)
ntbt_survfit(data, ...)
ntbt_survreg(data, ...)
ntbt_survSplit(data, ...)

Arguments

data

data frame, tibble, list, ...

...

Other arguments passed to the corresponding interfaced function.

Value

Object returned by interfaced function.

Details

Interfaces call their corresponding interfaced function.

Examples

## Not run: 
# library(intubate)
# library(magrittr)
# library(survival)
# 
# ## cch
# subcoh <- nwtco$in.subcohort
# selccoh <- with(nwtco, rel==1|subcoh==1)
# ccoh.data <- nwtco[selccoh,]
# ccoh.data$subcohort <- subcoh[selccoh]
# ccoh.data$histol <- factor(ccoh.data$histol,labels=c("FH","UH"))
# ccoh.data$stage <- factor(ccoh.data$stage,labels=c("I","II","III","IV"))
# ccoh.data$age <- ccoh.data$age/12 # Age in years
# 
# ## Original function to interface
# cch(Surv(edrel, rel) ~ stage + histol + age, data = ccoh.data,
#     subcoh = ~subcohort, id=~seqno, cohort.size=4028)
# 
# ## The interface reverses the order of data and formula
# ntbt_cch(data = ccoh.data, Surv(edrel, rel) ~ stage + histol + age,
#     subcoh = ~subcohort, id=~seqno, cohort.size=4028)
# 
# ## so it can be used easily in a pipeline.
# ccoh.data %>%
#   ntbt_cch(Surv(edrel, rel) ~ stage + histol + age,
#     subcoh = ~subcohort, id=~seqno, cohort.size=4028)
#     
# ## coxph    
# ## Original function to interface
# vet2 <- survSplit(Surv(time, status) ~., veteran,
#                   cut = c(60, 120), episode = "timegroup")
# coxph(Surv(tstart, time, status) ~ karno*strata(timegroup) +
#                 age + trt, data = vet2)
# 
# ## The interface reverses the order of data and formula
# vet2 <- ntbt_survSplit(veteran, Surv(time, status) ~.,
#                        cut = c(60, 120), episode = "timegroup")
# ntbt_coxph(data = vet2, Surv(tstart, time, status) ~
#               karno*strata(timegroup) + age + trt)
# 
# ## so it can be used easily in a pipeline.
# veteran %>%
#   ntbt_survSplit(Surv(time, status) ~.,
#                  cut = c(60, 120), episode = "timegroup") %>%
#   ntbt_coxph(Surv(tstart, time, status) ~ 
#              karno*strata(timegroup) + age + trt)
# 
# ## pyears
# hearta <- by(heart, heart$id,  
#              function(x)x[x$stop == max(x$stop),]) 
# hearta <- do.call("rbind", hearta) 
# 
# ## Original function to interface
# pyears(Surv(stop/365.25, event) ~
#          cut(age + 48, c(0,50,60,70,100)) + surgery,
#        data = hearta, scale = 1)
# 
# ## The interface reverses the order of data and formula
# ntbt_pyears(data = hearta,
#             Surv(stop/365.25, event) ~
#               cut(age + 48, c(0,50,60,70,100)) + surgery,
#             scale = 1)
# 
# ## so it can be used easily in a pipeline.
# hearta %>%
#   ntbt_pyears(Surv(stop/365.25, event) ~
#                 cut(age + 48, c(0,50,60,70,100)) + surgery,
#               scale = 1)
# 
# ## survConcordance
# ## Original function to interface
# survConcordance(Surv(time, status) ~ age, data=lung)
# 
# ## The interface reverses the order of data and formula
# ntbt_survConcordance(data=lung, Surv(time, status) ~ age)
# 
# ## so it can be used easily in a pipeline.
# lung %>%
#   ntbt_survConcordance(Surv(time, status) ~ age)
# 
# ## survexp
# ## Original function to interface
# fit1 <- survexp(futime ~ 1,data=jasa, 
#                 rmap=list(sex="male", year=accept.dt,   
#                           age=(accept.dt-birth.dt)),
#                 method='conditional')
# summary(fit1, times=1:10*182.5, scale=365)
# 
# ## The interface reverses the order of data and formula
# fit1 <- ntbt_survexp(data=jasa, futime ~ 1,
#                   rmap=list(sex="male", year=accept.dt,   
#                             age=(accept.dt-birth.dt)),
#                   method='conditional')
# summary(fit1, times=1:10*182.5, scale=365)
# 
# ## so it can be used easily in a pipeline.
# jasa %>%
#   ntbt_survexp(futime ~ 1,
#             rmap=list(sex="male", year=accept.dt,   
#                       age=(accept.dt-birth.dt)),
#             method='conditional') %>%
#   summary(times=1:10*182.5, scale=365)
# 
# ## survfit
# ## Original function to interface
# survfit(Surv(time, status) ~ x, data = aml)
# 
# ## The interface reverses the order of data and formula
# ntbt_survfit(data = aml, Surv(time, status) ~ x)
# 
# ## so it can be used easily in a pipeline.
# aml %>%
#   ntbt_survfit(Surv(time, status) ~ x)
# 
# aml %>%
#   ntbt_survfit(Surv(time, status) ~ x) %>%
#   plot(lty = 2:3)
# 
# 
# ## survreg
# ## Original function to interface
# survreg(Surv(time, status) ~ ph.ecog + age + strata(sex), lung)
# 
# ## The interface reverses the order of data and formula
# ntbt_survreg(lung, Surv(time, status) ~ ph.ecog + age + strata(sex))
# 
# ## so it can be used easily in a pipeline.
# lung %>%
#   ntbt_survreg(Surv(time, status) ~ ph.ecog + age + strata(sex))
# 
# ## survSplit
# ## Original function to interface
# vet2 <- survSplit(Surv(time, status) ~., veteran,
#                   cut = c(60, 120), episode = "timegroup")
# coxph(Surv(tstart, time, status) ~ karno*strata(timegroup) +
#                 age + trt, data = vet2)
# 
# ## The interface reverses the order of data and formula
# vet2 <- ntbt_survSplit(veteran, Surv(time, status) ~.,
#                        cut = c(60, 120), episode = "timegroup")
# ntbt_coxph(data = vet2, Surv(tstart, time, status) ~
#            karno*strata(timegroup) + age + trt)
# 
# ## so it can be used easily in a pipeline.
# veteran %>%
#   ntbt_survSplit(Surv(time, status) ~.,
#                  cut = c(60, 120),
#                  episode = "timegroup") %>%
#   ntbt_coxph(Surv(tstart, time, status) ~ 
#              karno*strata(timegroup) + age + trt)
# ## End(Not run)