sievePH: Semiparametric Estimation of Coefficients in a Mark-Specific...

Description Usage Arguments Details Value References See Also Examples

View source: R/sievePH.R

Description

sievePH implements the semiparametric estimation method of Juraska and Gilbert (2013) for the multivariate mark- specific hazard ratio in the competing risks failure time analysis framework. It employs (i) the semiparametric method of maximum profile likelihood estimation in the treatment-to-placebo mark density ratio model (Qin, 1998) and (ii) the ordinary method of maximum partial likelihood estimation of the overall log hazard ratio in the Cox model. sievePH requires that the multivariate mark data are fully observed in all failures.

Usage

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sievePH(eventTime, eventInd, mark, tx)

Arguments

eventTime

a numeric vector specifying the observed right-censored time to the event of interest

eventInd

a numeric vector indicating the event of interest (1 if event, 0 if right-censored)

mark

either a numeric vector specifying a univariate continuous mark or a data frame specifying a multivariate continuous mark. No missing values are permitted for subjects with eventInd = 1. For subjects with eventInd = 0, the value(s) in mark should be set to NA.

tx

a numeric vector indicating the treatment group (1 if treatment, 0 if placebo)

Details

sievePH considers data from a randomized placebo-controlled treatment efficacy trial with a time-to-event endpoint. The parameter of interest, the mark-specific hazard ratio, is the ratio (treatment/placebo) of the conditional mark-specific hazard functions. It factors as the product of the mark density ratio (treatment/placebo) and the ordinary marginal hazard function ignoring mark data. The mark density ratio is estimated using the method of Qin (1998), while the marginal hazard ratio is estimated using coxph() in the survival package. Both estimators are consistent and asymptotically normal. The joint asymptotic distribution of the estimators is detailed in Juraska and Gilbert (2013).

Value

An object of class sievePH which can be processed by summary.sievePH to obtain or print a summary of the results. An object of class sievePH is a list containing the following components:

References

Juraska, M. and Gilbert, P. B. (2013), Mark-specific hazard ratio model with multivariate continuous marks: an application to vaccine efficacy. Biometrics 69(2):328<e2><80><93>337.

Qin, J. (1998), Inferences for case-control and semiparametric two-sample density ratio models. Biometrika 85, 619<e2><80><93>630.

See Also

summary.sievePH, plot.summary.sievePH, testIndepTimeMark and testDensRatioGOF

Examples

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n <- 500
tx <- rep(0:1, each=n/2)
tm <- c(rexp(n/2, 0.2), rexp(n/2, 0.2 * exp(-0.4)))
cens <- runif(n, 0, 15)
eventTime <- pmin(tm, cens, 3)
eventInd <- as.numeric(tm <= pmin(cens, 3))
mark1 <- ifelse(eventInd==1, c(rbeta(n/2, 2, 5), rbeta(n/2, 2, 2)), NA)
mark2 <- ifelse(eventInd==1, c(rbeta(n/2, 1, 3), rbeta(n/2, 5, 1)), NA)

# fit a model with a univariate mark
fit <- sievePH(eventTime, eventInd, mark1, tx)

# fit a model with a bivariate mark
fit <- sievePH(eventTime, eventInd, data.frame(mark1, mark2), tx)

sievePH documentation built on Jan. 11, 2020, 9:18 a.m.