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

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The GofCens package include the following graphical tools and goodness-of-fit tests for right-censored data:

These functions share several features as they can handle both complete and right-censored data, and they provide parameter estimates for the distributions under study.

Installation

GofCens can be installed from CRAN:

install.packages("GofCens")

Brief Example

To conduct goodness-of-fit tests with right censored data we can use the KScens(), CvMcens(), ADcens() and chisqcens() functions. We illustrate this by means of the colon dataset:

# Kolmogorov-Smirnov
set.seed(123)
KScens(Surv(time, status) ~ 1, colon, distr = "norm")

# Cramér-von Mises
colonsamp <- colon[sample(nrow(colon), 300), ]
CvMcens(Surv(time, status) ~ 1, colonsamp, distr = "normal")

# Anderson-Darling
ADcens(Surv(time, status) ~ 1, colonsamp, distr = "normal")

# Generalized chi-squared-type test
chisqcens(Surv(time, status) ~ 1, colonsamp, M = 6, distr = "normal")

The graphical tools provide nice plots via the functions cumhazPlot(), kmPlot() and probPlot(). See several examples using the nba data set:

data(nba)
cumhazPlot(Surv(survtime, cens) ~ 1, nba, distr = c("expo", "normal", "gumbel"))
kmPlot(Surv(survtime, cens) ~ 1, nba, distr = c("normal", "weibull", "lognormal"),
       prnt = FALSE)
probPlot(Surv(survtime, cens) ~ 1, nba, "lognorm", plots = c("PP", "QQ", "SP"),
         ggp = TRUE, m = matrix(1:3, nr = 1))

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