dataDIVAT3: A Third Sample From the DIVAT Data Bank.

In RISCA: Causal Inference and Prediction in Cohort-Based Analyses

A Third Sample From the DIVAT Data Bank.

Description

A data frame with 4267 French kidney transplant recipients.

Usage

data(dataDIVAT3)

Format

A data frame with 4267 observations for the 8 following variables.

ageR

This numeric vector represents the age of the recipient (in years)

sexeR

This numeric vector represents the gender of the recipient (1=men, 0=female)

year.tx

This numeric vector represents the year of the transplantation

ante.diab

This numeric vector represents the diabetes statute (1=yes, 0=no)

pra

This numeric vector represents the pre-graft immunization using the panel reactive antibody (1=detectable, 0=undetectable)

ageD

This numeric vector represents the age of the donor (in years)

death.time

This numeric vector represents the follow up time in days (until death or censoring)

death

This numeric vector represents the death indicator at the follow-up end (1=death, 0=alive)

Source

URL: www.divat.fr

References

Le Borgne et al. Standardized and weighted time-dependent ROC curves to evaluate the intrinsic prognostic capacities of a marker by taking into account confounding factors. Manuscript submitted. Stat Methods Med Res. 27(11):3397-3410, 2018. <doi: 10.1177/ 0962280217702416.>

Examples

data(dataDIVAT3)

### a short summary of the recipient age at the transplantation
summary(dataDIVAT3$ageR)

### Kaplan and Meier estimation of the recipient survival
plot(survfit(Surv(death.time/365.25, death) ~ 1, data = dataDIVAT3),
 xlab="Post transplantation time (in years)", ylab="Patient survival",
 mark.time=FALSE)

RISCA documentation built on April 4, 2025, 3:52 a.m.