ypreg {YPmodelPhreg} | R Documentation |
Fit a short-term and long-term hazard ratio model with proportional adjustment
Description
The main results of the function are the estimations of:
parameters in the covariate-adjusted short-term and long-term hazard ratio model with confidence intervals;
the average hazard ratio with the confidence interval; and
the hazard ratio function along with point-wise and simultaneous confidence bands (confidence intervals for the hazard ratios at specific user input time points are also given).
Usage
## Default S3 method:
ypreg(data, alpha = 0.05, time.hr = NULL,
L = NULL, U = NULL, repnum = 5000, tau = NULL, ...)
Arguments
... |
for S4 method only. |
data |
A numeric matrix containing all variables in the data set. The columns must follow this order: 1) time until event or censoring, 2) censoring status (1 = event, 0 = censored), 3) binary group indicator taking values of 0 and 1 (e.g., 1 = treatment, 0 = control for a randomized trial), and 4) a set of numeric vectors of covariates. See the data structure of |
alpha |
A numeric value for the significance level. The default is |
time.hr |
A numeric vector of time points at which hazard ratios will be estimated along with confidence intervals. |
L |
A numeric value for the lower bound of the range [ |
U |
A numeric value for the upper bound of the range [ |
repnum |
The number of replications for the re-sampling method. The default is |
tau |
A numeric value for the maximum follow-up time. The default is |
Details
The confidence intervals for the hazard ratios are obtained using the logarithmic transformation. When the user input interval [L
, U
] is different from the default interval, the intersection of the user input interval and the default interval is used. The point-wise confidence intervals and the simultaneous confidence bands can be plotted by supplying the object being returned by the function ypreg
to the function plot.ypreg
.
Value
an object of S3 ypreg
class representing the fit. The object also includes the results of the Cox proportional hazards model, implemented by using the coxph
function in the survival
library.
A list with at least the following elements:
fit_coxph |
estimation results from the Cox proportional hazards model |
best_b0 |
the estimates from the short-term and long-term hazard ratio model without proportional adjustment |
best_ypx |
the estimates from the short-term and long-term hazard ratio model with proportional adjustment |
res_summ |
summary of estimation results with the covariate-adjusted short-term and long-term hazard ratio model |
res_hrci |
estimation results of hazard ratios at |
References
Yang, S., & Prentice, R. (2005). Semiparametric analysis of short-term and long-term hazard ratios with two-sample survival data. Biometrika, 92(1), 1-17.
Yang, S., & Prentice, R. L. (2015). Assessing potentially time-dependent treatment effect from clinical trials and observational studies for survival data, with applications to the Women's Health Initiative combined hormone therapy trial. Statistics in medicine, 34(11), 1801-1817.
See Also
Examples
library(YPmodelPhreg)
data(colonexample)
head(colonexample)
res <- ypreg(colonexample, time.hr = c(1, 7))
res
plot(res)