Package 'surv2sampleComp'

Title: Inference for Model-Free Between-Group Parameters for Censored Survival Data
Description: Performs inference of several model-free group contrast measures, which include difference/ratio of cumulative incidence rates at given time points, quantiles, and restricted mean survival times (RMST). Two kinds of covariate adjustment procedures (i.e., regression and augmentation) for inference of the metrics based on RMST are also included.
Authors: Lu Tian, Hajime Uno, Miki Horiguchi
Maintainer: Miki Horiguchi <[email protected]>
License: GPL-2
Version: 1.0-5
Built: 2025-02-15 03:54:46 UTC
Source: https://github.com/cran/surv2sampleComp

Help Index


Inference for Model-Free Between-Group Parameters For Censored Survival Data

Description

Performs inference of several model-free group contrast measures, which include difference/ratio of cumulative incidence rates at given time points, quantiles, and restricted mean survival times (RMST). Two kinds of covariate adjustment procedures (i.e., regression and augmentation) for inference of the metrics based on RMST are also included.

Author(s)

Lu Tian, Hajime Uno, Miki Horiguchi

Maintainer: Miki Horiguchi <[email protected]>

References

Tian L, Zhao L, Wei LJ. Predicting the restricted mean event time with the subject's baseline covariates in survival analysis. Biostatistics 2014, 15, 222-233.

Zhao L, Tian L, Uno H, Solomon S, Pfeffer M, Schindler J, Wei LJ. Utilizing the integrated difference of two survival functions to quantify the treatment contrast for designing, monitoring, and analyzing a comparative clinical study. Clinical Trials 2012, 9, 570-577.

See Also

flexsurv plotrix survival


Edit pbc data to run sample code

Description

Edit pbc data in survival package and make it ready to run the sample code in this manual.

Usage

pbc.sample()

See Also

pbc in survival package


Plot method for surv2sample objects

Description

Creates plots from a surv2sample object.

Usage

## S3 method for class 'surv2sample'
plot(x, measure = NULL, baseline = 0, ...)

Arguments

x

surv2sample object

measure

The type of measure used for the plot. When default(=NULL), plot.survfit() is called and KM plots are given. When "relative time" is specified, a plot of relative percentiles with corresponidng 0.95 confidence intervals is generatead.

baseline

Indicates the baseline group, 0/1. Default is 0.

...

For further method

See Also

plotCI in plotrix package


Adjusted difference/ratio of restricted mean survival times

Description

Compares restricted mean survival time between two groups, adjusting for imbalance of baseline factors.

Usage

rmstaug(y, delta, x, arm, tau, type="difference", conf.int=0.95)

Arguments

y

The follow-up time.

delta

The censoring indicator, 1=event, and 0=censoring.

x

The covariate matrix. The group indicator, arm (below) should not be included in this matrix.

arm

The group indicator, 1/0.

tau

The value indicates the restricted time point on the follow-up time to calculate the restricted mean survival time.

type

The type of the between-group contrast measure: "difference"(default), "ratio" or "lossratio".

conf.int

The level for computation of the confidence intervals. The default is 0.95.

Author(s)

Lu Tian

References

Tian L, Zhao L, Wei LJ. Predicting the restricted mean event time with the subject's baseline covariates in survival analysis. Biostatistics 2014, 15, 222-233.

Examples

D=pbc.sample()
rmstaug(D$time, D$status, D$covariates, D$group, tau=8, type="difference")

Adjusted difference/ratio of restricted mean survival times

Description

Compares restricted mean survival time between two groups, adjusting for imbalance of baseline factors via a regression model.

Usage

rmstreg(y, delta, x, arm, tau, type="difference", conf.int=0.95)

Arguments

y

The follow-up time.

delta

The censoring indicator, 1=event, and 0=censoring.

x

The covariate matrix. The first colomn of this matrix should be the group indicator, arm (below).

arm

The group indicator, 1/0.

tau

The value indicates the restricted time point on the follow-up time to calculate the restricted mean survival time.

type

The type of the between-group contrast measure: "difference"(default), "ratio" or "lossratio".

conf.int

The level for computation of the confidence intervals. The default is 0.95.

Author(s)

Lu Tian

References

Tian L, Zhao L, Wei LJ. Predicting the restricted mean event time with the subject's baseline covariates in survival analysis. Biostatistics 2014, 15, 222-233.

Examples

D=pbc.sample()
x=cbind(D$group, D$covariates)
rmstreg(D$time, D$status, x, D$group, tau=8, type="difference")

Inference of model-free between-group contrasts with censored survival data

Description

Performs inference of several model-free group contrast measures, which include difference/ratio of cumulative incidence rates, quantiles, restricted mean survival times (RMST), and integrated survival rates.

Usage

surv2sample(time, status, arm, npert=1000,
                    timepoints=c(12, 24, 36, 40), quanprobs=c(0.1, 0.15, 0.2),
                    tau_start=0, tau, SEED=NULL, procedure="KM", conf.int=0.95)

Arguments

time

The follow-up time.

status

The censoring indicator, 1=event, and 0=censoring.

arm

The indicator for groups to compare 1/0.

npert

The number of resampling. The default is 1000.

timepoints

specifies the time points at which difference and ratio of the survival rates are computed.

quanprobs

specifies the probabilities at which difference and ratio of the corresponding quantiles are computed.

tau_start

The value indicates time point on the follow-up time to calculate the restricted mean survival time beyond the time point. The default is 0.

tau

The value indicates the restricted time point on the follow-up time to calculate the restricted mean survival time. (i.e., the minimum of the largest observed time in each of the two groups)

SEED

A random seed used for the resampling. Default is NULL.

procedure

Specifies the inference procedure. A non-parametric procedure by the method of Kaplan-Meier ("KM") is the default. Another option is a parametric inference procedure by fitting a generalized gamma distribution to each group ("GG").

conf.int

The level for computation of the confidence intervals. The default is 0.95.

Author(s)

Hajime Uno, Miki Horiguchi

References

Tian L, Zhao L, Wei LJ. Predicting the restricted mean event time with the subject's baseline covariates in survival analysis. Biostatistics 2014, 15, 222-233.

Zhao L, Tian L, Uno H, Solomon S, Pfeffer M, Schindler J, Wei LJ. Utilizing the integrated difference of two survival functions to quantify the treatment contrast for designing, monitoring, and analyzing a comparative clinical study. Clinical Trials 2012, 9, 570-577.

Examples

D=pbc.sample()
surv2sample(D$time, D$status, D$group, npert=500, timepoints=c(2,4,6,8),
quanprobs =c(0.2, 0.3), tau=8, procedure="KM")