KScens | R Documentation |
Function KScens
computes the Kolmogorov-Smirnov statistic and p-value for
right-censored data against eight possible predefined or user-specified distributions
using either bootstrapping or a modified test. This function also accounts for
complete data.
## Default S3 method:
KScens(times, cens = rep(1, length(times)),
distr = c("exponential", "gumbel", "weibull", "normal",
"lognormal", "logistic", "loglogistic", "beta"),
betaLimits = c(0, 1), igumb = c(10, 10), BS = 999,
params0 = list(shape = NULL, shape2 = NULL, location = NULL,
scale = NULL, theta = NULL),
tol = 1e-04, boot = TRUE, start = NULL, ...)
## S3 method for class 'formula'
KScens(formula, data, ...)
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 ( |
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. |
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 |
boot |
Logical to indicate if the p-value is computed using bootstrapping or using the
the modified Kolmogorov-Smirnov test (see details). Default is |
start |
A named list giving the initial values of parameters of the named distribution or a function of data computing initial values and returning a named list. This argument may be omitted (default) for the eight prespecified distributions. See more details in mledist. |
... |
Additional arguments for the |
By default the p-value is computed via bootstrapping methods.
The parameter estimation is acomplished with the fitdistcens
function of the fitdistrplus package.
To avoid long computation times due to bootstrapping, an alternative
with complete data is the function ks.test
of the stats package.
The precision of the survival times is important mainly in the data generation step of the bootstrap samples.
If boot = FALSE
a modified test is used to compute the p-value.
Fleming et al. (1980) proposed a modified Kolmogorov-Smirnov test to use
with right-censored data. This function reproduces this test for a
given survival data and a theorical distribution. The approximation for
the p-value is acceptable when it is smaller than 0.8 and excellent when
it is smaller than 0.2. The output of the function follows the notation
of Fleming et al. (1980).
In presence of ties, different authors provide slightly different
definitions of \widehat{F}_n(t)
, with which other values of
the test statistic might be obtained.
KScens
returns an object of class "KScens"
.
An object of class "KScens"
is a list containing the following components:
Distribution |
Null distribution. |
Hypothesis |
Parameters under the null hypothesis (if |
Test |
Vector containing the value of the modified Kolmogorov-Smirnov statistic ( |
Estimates |
Vector with the maximum likelihood estimates of the parameters of the distribution under study. |
StdErrors |
Vector containing the estimated standard errors. |
aic |
The Akaike information criterion. |
bic |
The so-called BIC or SBC (Schwarz Bayesian criterion). |
BS |
The number of bootstrap samples used. If the modified test is used, a 0 is returned. |
K. Langohr, M. Besalú, M. Francisco, A. Garcia, G. Gómez.
T. R. Fleming et al. Modified Kolmogorov-Smirnov test procedure with application to arbitrarily right-censored data. In: Biometrics 36 (1980), 607-625. URL: https://doi.org/10.2307/2556114
Function ks.test (Package stats) for complete data and gofcens for statistics and p-value of Kolmogorov-Smirnov, Cramér von-Mises and Anderson-Darling together for right-censored data.
# Complete data with bootstrapping
set.seed(123)
KScens(times = rweibull(100, 12, scale = 4), distr = "weibull", BS = 99)
# Censored data with bootstrapping
KScens(Surv(time, status) ~ 1, colon, distr = "norm", BS = 99)
# Censored data using the modified test
KScens(Surv(time, status) ~ 1, colon, distr = "norm", boot = FALSE)
data(nba)
summary(KScens(Surv(survtime, cens) ~ 1, nba, "logis", boot = FALSE), degs = 2)
KScens(Surv(survtime, cens) ~ 1, nba, "beta", betaLimits = c(0, 80),
boot = FALSE)
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