README.md

In MartaBofillRoig/SurvBin: Two-sample statistics for binary and time-to-event outcomes

SurvBin Package

Background

We propose a class of two-sample statistics for testing the equality of proportions and the equality of survival functions. We build our proposal on a weighted combination of a score test for the difference in proportions and a Weighted Kaplan-Meier statistic-based test for the difference of survival functions. The proposed statistics are fully non-parametric and do not rely on the proportional hazards assumption for the survival outcome.

We implemented the proposed statistics in the R package SurvBin.

Description

The SurvBin package contains four key functions:

• lstats to compute the standardized L-statistic (with pooled/unpooled variance estimators);
• lstats_boots to compute the standardized L-statistic (with bootstrap variance estimator);
• survtest to compute the Weighted Kaplan-Meier based-test;
• bintest to compute the proportions' test.

The SurvBin package also provides the function survbinCov that can be used to calculate the covariance between the survival and binary statistics; and the function simsurvbin for simulating bivariate binary and survival data.

More information can be found at: https://martabofillroig.github.io/SurvBin/ (see Reference tab).

Installation

# install.packages("devtools")
library(devtools)
install_github("MartaBofillRoig/SurvBin")

References

This repository also contains the source files of the preprint:

• "A class of two-sample nonparametric statistics for binary and time-to-event outcomes". Marta Bofill Roig, Guadalupe Gómez Melis. (2020). https://arxiv.org/abs/2002.01369

Specifically, in the folder CODE_paper/CaseStudy, there is the source code for reproduce the illustration; and in the folder CODE_paper/Simulations, there is the code to reproduce the simulation study (see Simulations subfolder).

MartaBofillRoig/SurvBin documentation built on Sept. 29, 2021, 5:18 p.m.