View source: R/summary.sievePH.R
summary.sievePH | R Documentation |
summary
method for an object of class sievePH
.
## S3 method for class 'sievePH' summary( object, markGrid, contrast = c("te", "hr", "loghr"), sieveAlternative = c("twoSided", "oneSided"), confLevel = 0.95, ... ) ## S3 method for class 'summary.sievePH' print(x, digits = 4, ...)
object |
an object of class |
markGrid |
a matrix specifying a grid of multivariate mark values, where rows correspond to different values on the (multivariate) grid and columns correspond to components of the mark. A numeric vector is allowed
for univariate marks. The point and interval estimates of the |
contrast |
a character string specifying the treatment effect parameter of interest. The default value is |
sieveAlternative |
a character string specifying the alternative hypothesis for the sieve tests, which can be either |
confLevel |
the confidence level (0.95 by default) of reported confidence intervals |
... |
further arguments passed to or from other methods |
x |
an object of class |
digits |
the number of significant digits to use when printing (4 by default) |
print.summary.sievePH
prints a formatted summary of results. Inference about coefficients in the mark-specific proportional hazards model is tabulated. Additionally, a summary is generated
from the likelihood-ratio and Wald tests of two relevant null hypotheses: (1) {H_0: HR(v)=1 for all v}, and (2) {H_0: HR(v)=HR for all v}. For the tests of (2) and a univariate
mark, sieveAlternative
controls the choice of the alternative hypothesis.
An object of class summary.sievePH
, which is a list with the following components:
coef
: a data frame summarizing point and interval estimates of the density ratio model coefficients and the marginal log hazard ratio (the confidence level is specified by confLevel
), and p-values from the
two-sided Wald test of the null hypothesis that the parameter equals zero
pLR.HRunity.2sided
: a numeric vector with two named components: pLR.dRatio.2sided
is a p-value from the two-sided profile likelihood-ratio test of the null hypothesis H_0: β=0, where β is the
vector of mark coefficients in the mark density ratio model, and pLR.cox.2sided
is a p-value from the two-sided partial likelihood-ratio test of the null hypothesis H_0: γ=0, where γ is the
marginal log hazard ratio in the Cox model. The two p-values are intended for the use of the Simes (1986) procedure as described on page 4 in Juraska and Gilbert (2013).
pWald.HRunity.2sided
: a p-value from the two-sided Wald test of the null hypothesis {H_0: HR(v)=1 for all v}
pWtWald.HRunity.1sided
: a p-value from the one-sided weighted Wald test of the null hypothesis {H_0: HR(v)=1 for all v} against the alternative hypothesis {H_1: HR < 1 and HR(v) is
increasing in each component of v}
pLR.HRconstant.2sided
: a p-value from the two-sided profile likelihood-ratio test of the null hypothesis {H_0: HR(v)=HR for all v}. This component is available if sieveAlternative="twoSided"
.
pLR.HRconstant.1sided
: a numeric vector with two named components: pLR.dRatio.2sided
is a p-value from the two-sided profile likelihood-ratio test of the null hypothesis {H_0: HR(v)=HR for all v},
and estBeta
is the point estimate of the univariate mark coefficient in the density ratio model. This component is available if the mark is univariate and sieveAlternative="oneSided"
.
pWald.HRconstant.2sided
: a p-value from the two-sided Wald test of the null hypothesis {H_0: HR(v)=HR for all v}. This component is available if sieveAlternative="twoSided"
.
pWald.HRconstant.1sided
: a p-value from the one-sided Wald test of the null hypothesis {H_0: HR(v)=HR for all v} against the alternative hypothesis {H_1: HR(v) is increasing in v}.
This component is available if the mark is univariate and sieveAlternative="oneSided"
.
te
: a data frame summarizing point and interval estimates of the mark-specific treatment efficacy on the grid of mark values in markGrid
(available if contrast="te"
). The confidence level is specified
by confLevel
.
hr
: a data frame summarizing point and interval estimates of the mark-specific hazard ratio on the grid of mark values in markGrid
(available if contrast="hr"
). The confidence level is specified by
confLevel
.
te
: a data frame summarizing point and interval estimates of the mark-specific log hazard ratio on the grid of mark values in markGrid
(available if contrast="loghr"
). The confidence level is specified by
confLevel
.
Juraska, M. and Gilbert, P. B. (2013), Mark-specific hazard ratio model with multivariate continuous marks: an application to vaccine efficacy. Biometrics 69(2):328–337.
sievePH
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 bivariate mark fit <- sievePH(eventTime, eventInd, data.frame(mark1, mark2), tx) sfit <- summary(fit, markGrid=matrix(c(0.3, 0.3, 0.6, 0.3, 0.3, 0.6, 0.6, 0.6), ncol=2, byrow=TRUE)) # print the formatted summary sfit # treatment efficacy estimates on the grid sfit$te
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