gofcens: Kolmogorov-Smirnov, Crámer-von Mises, and Anderson-Darling...

In GofCens: Goodness-of-Fit Methods for Right-Censored Data

Description

gofcens computes the Kolmogorov-Smirnov, Crámer-von Mises, and Anderson-Darling statistics for complete and right-censored data against eight possible distributions.

Usage

gofcens(times, cens = rep(1, length(times)), 
        distr = c("exponential", "gumbel", "weibull", "normal", 
                  "lognormal", "logistic", "loglogistic", "beta"), 
        betaLimits = c(0, 1), igumb = c(10, 10), degs = 4, 
        params = list(shape = NULL, shape2 = NULL, location = NULL, 
                      scale = NULL))

Arguments

times	Numeric vector of times until the event of interest.
cens	Status indicator (1, exact time; 0, right-censored time). If not provided, all times are assumed to be exact.
distr	A string specifying the name of the distribution to be studied. The possible distributions are the exponential ("exponential"), the Weibull ("weibull"), the Gumbel ("gumbel"), the normal ("normal"), the lognormal ("lognormal"), the logistic ("logistic"), the loglogistic ("loglogistic"), and the beta ("beta") distribution.
betaLimits	Two-components vector with the lower and upper bounds of the Beta distribution. This argument is only required, if the beta distribution is considered.
igumb	Two-components vector with the initial values for the estimation of the Gumbel distribution parameters.
degs	Integer indicating the number of decimal places of the numeric results of the output.
params	List specifying the parameters of the theoretical distribution. By default, parameters are set to NULL and estimated with the maximum likelihood method. This argument is only considered, if all parameters of the studied distribution are specified.

Details

Fleming et al. (1980) proposed a modified Kolmogorov-Smirnov test to be used with right-censored data. Koziol and Green (1976) proposed a Crámer-von Mises statistic for randomly censored data. This function reproduces this test for a given survival data and a theorical distribution. In presence of ties, different authors provide slightly different definitions of the product-limit estimator, what might provide different values of the test statistic.

When dealing with complete data, we recommend the use of functions ks.test of the stats package and cvm.test and ad.test of the goftest package.

Value

A list containing the following components

Tests statistics	Values of the Kolmogovor-Smirnov, Crámer-von Mises, and Anderson-Darling test statistics
Distribution	Null distribution
Parameters	List with the maximum likelihood estimates of the parameters of the distribution under study.

Author(s)

K. Langohr, M. Besalú, G. Gómez.

References

T. R. Fleming et al. Modified Kolmogorov-Smirnov test procedure with application to arbitrarily right-censored data. In: Biometrics 36 (1980), 607-625.

J. A. Koziol and S. B. Green. A Crámer-von Mises statistic for randomly censored data. In: Biometrika, 63 (3) (1976), 465-474.

A. N. Pettitt and M. A. Stephens. Modified Crámer-von Mises statistics for censored data. In: Biometrika, 63 (2) (1976), 291-298.

See Also

ks.test (Package stats), cvm.test (Package goftest), and ad.test (Package goftest) for complete data, and KScens for the Kolmogorov-Smirnov test for right-censored data, which returns the p-value.

Examples

# Complete data
set.seed(123)
gofcens(times = rweibull(1000, 12, scale = 4), distr = "weibull")

# Censored data
library(survival)
gofcens(aml$time, aml$status, distr = "norm")

data(nba)
gofcens(nba$survtime, nba$cens, "lognorm")
gofcens(nba$survtime, nba$cens, "norm")

GofCens documentation built on Jan. 6, 2022, 1:06 a.m.