chisqcens {GofCens} | R Documentation |
General chi-squared statistics for right-censored data.
Description
Function chisqcens
computes the general chi-squared test statistic for
right-censored data introduced by Kim (1993) and the respective p-value
using bootstrapping.
Usage
## Default S3 method:
chisqcens(times, cens = rep(1, length(times)), M,
distr = c("exponential", "gumbel", "weibull", "normal",
"lognormal", "logistic", "loglogistic", "beta"),
betaLimits=c(0, 1), igumb = c(10, 10), degs = 3, BS = 999,
params0 = list(shape = NULL, shape2 = NULL,
location = NULL, scale = NULL), tol = 1e-04, ...)
## S3 method for class 'formula'
chisqcens(formula, data,...)
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. |
M |
Number indicating the number of cells that will be considered. |
distr |
A string specifying the name of the distribution to be studied.
The possible distributions are the exponential ( |
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. |
BS |
Number of bootstrap samples. |
params0 |
List specifying the parameters of the theoretical distribution.
By default, parameters are set to |
tol |
Precision of survival times. |
formula |
A formula with a numeric vector as response (which assumes no censoring) or |
data |
Data frame for variables in |
... |
Additional arguments. |
Details
The function implements the test introduced by Kim (1993) and returns the value of the test statistic.
The cell boundaries of the test are obtained via the quantiles, which
are based on the Kaplan-Meier estimate of the distribution function.
In the presence of right-censored data, it is possible that not all
quantiles are estimated, and in this case, the value of M
provided by the user is reduced.
The parameter estimation is acomplished with the fitdistcens
function of the fitdistrplus package.
The precision of the survival times is important mainly in the data generation step of the bootstrap samples.
Value
chisqcens
returns an object of class "chisqcens"
.
An object of class "chisqcens"
is a list containing the following components:
Distribution |
Null distribution. |
Null hypothesis |
Parameters under the null hypothesis (if |
Statistic |
Value of the test statistic. |
p-value |
Estimated p-value. |
Parameters |
The values of the parameters of the null distribution. If the user has set the parameters manually, these will be the returned parameters, otherwise the maximum likelihood estimates are returned. |
CellNumber |
Vector with two values: the original cell number introduced by the user and the final cell number used. |
Author(s)
K. Langohr, M. Besalú, M. Francisco, G. Gómez.
References
J. H. Kim. Chi-Square Goodness-of-Fit Tests for Randomly Censored Data. In: The Annals of Statistics, 21 (3) (1993), 1621-1639.
Examples
# Complete data
set.seed(123)
chisqcens(times = rgumbel(100, 12, scale = 4), M = 8, distr = "gumbel",
BS = 99)
## Not run:
# Censored data
data(colon)
set.seed(123)
colonsamp <- colon[sample(nrow(colon), 300), ]
chisqcens(Surv(time, status) ~ 1, colonsamp, M = 6, distr = "normal")
## End(Not run)