Hazard ratio as a function of time from a parametric survival model
Source:R/hr_flexsurvreg.R
hr_flexsurvreg.RdHazard ratio as a function of time from a parametric survival model
Usage
hr_flexsurvreg(
x,
newdata = NULL,
t = NULL,
start = 0,
ci = TRUE,
B = 1000,
cl = 0.95,
na.action = na.pass
)Arguments
- x
Object returned by
flexsurvregorflexsurvspline.- newdata
A data frame with two rows, each specifying a set of covariate values. The hazard ratio is calculated as hazard(z2)/hazard(z1), where z1 is the first row of
newdataand z2 is the second row.newdatamust be supplied unless the modelxincludes just one covariate. With one covariate, a default is constructed, which defines the hazard ratio between the second and first level of the factor (if the covariate is a factor), or between a value of 1 and a value of 0 (if the covariate is numeric).- t
Times to calculate fitted values for. By default, these are the sorted unique observation (including censoring) times in the data - for left-truncated datasets these are the "stop" times.
- start
Optional left-truncation time or times. The returned survival, hazard or cumulative hazard will be conditioned on survival up to this time. Predicted times returned with
"rmst","mean","median"or"quantile"will be times since time zero, not times since thestarttime.A vector of the same length as
tcan be supplied to allow different truncation times for each prediction time, though this doesn't make sense in the usual case where this function is used to calculate a predicted trajectory for a single individual. This is why the defaultstarttime was changed for version 0.4 of flexsurv - this was previously a vector of the start times observed in the data.- ci
Set to
FALSEto omit confidence intervals.- B
Number of simulations from the normal asymptotic distribution of the estimates used to calculate confidence intervals or standard errors. Decrease for greater speed at the expense of accuracy, or set
B=0to turn off calculation of CIs and SEs.- cl
Width of symmetric confidence intervals, relative to 1.
- na.action
Function determining what should be done with missing values in
newdata. Ifna.pass(the default) then summaries ofNAare produced for missing covariate values. Ifna.omit, then missing values are dropped, the behaviour ofsummary.flexsurvregbeforeflexsurvversion 1.2.