pmcc: Product-Moment Correlation Coefficient

Description Usage Arguments See Also Examples

View source: R/pmcc.R

Description

pmcc computes the conditional product-moment correlation coefficient proposed by Chen et al. (1996). The conditional product-moment correlation coefficient uses only the uncensored events.

Usage

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pmcc(trun, obs, a = 0, trans = "linear")

Arguments

trun

left truncation time satisfying trun <= obs.

obs

observed failure time, must be the same length as trun, might be right-censored.

a

a numeric transformation parameter. The default value is 0, which applies no transformation. This parameter must be greater than -1. See ?tranSurvfit for the transformation model structure.

trans

a character string specifying the transformation structure. The following are permitted:

linear

linear transformation structure,

log

log-linear transformation structure,

exp

exponential transformation structure.

See Also

trSurvfit

Examples

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## Generate simulated data from transformation model
datgen <- function(n) {
    a <- -0.3
    X <- rweibull(n, 2, 4) ## failure times
    U <- rweibull(n, 2, 1) ## latent truncation time
    T <- (1 + a) * U - a * X ## apply transformation
    C <- rlnorm(n, .8, 1) ## censoring
    dat <- data.frame(trun = T, obs = pmin(X, C), delta = 1 * (X <= C))
    return(subset(dat, trun <= obs))
}

set.seed(123)
dat <- datgen(300)
with(dat, pmcc(trun, obs))

stc04003/tranSurv documentation built on Oct. 22, 2018, 7:26 p.m.