jp.plot.surv: Plot of conditional survival versus interval

In JPSurv: Joinpoint Model for Relative and Cause-Specific Survival

Plot of conditional survival versus interval

Description

Plot of conditional survival versus interval

Usage

jp.plot.surv(fit.uncond, fit.cond, start.interval=NULL, end.interval=NULL,
                    year.col="Year", interval.col="Interval", 
                    relSurvInt.col="Relative_Survival_Interval", addToYear=0,
                    ylim=NULL, yearsToPlot=NULL, legend.pos="bottom")

Arguments

fit.uncond	Object returned from joinpoint.
fit.cond	Object returned from joinpoint.conditional.
start.interval	NULL or the starting interval. If NULL, then the smallest starting interval will be chosen.
end.interval	NULL or the ending interval. If NULL, then the largest interval will be chosen.
year.col	The name of the year at diagnosis column in fit.cond. The default is "Year".
interval.col	The name of the interval column in fit.cond. The default is "Interval".
relSurvInt.col	The name of the relative survival interval column in fit.cond. The default is "Relative_Survival_Interval".
addToYear	Integer to add to the year at diagnosis column to give the correct years at diagnosis for displaying. The default is 0.
ylim	NULL or the y-axis limits of the plot. If NULL, then the limits will be determined from the data.
yearsToPlot	NULL or the years at diagnosis to display in the plot. If NULL, then no more than five years will be selected for the plot.
legend.pos	Character string to give the legend position in the plot. The default is "bottom".

Details

The lines on the plot use the pred_cum column in fit.cond, while the points are from the relSurvInt.col column.

Value

NULL

See Also

joinpoint, joinpoint.conditional

Examples

#Load the provided SEER 18 breast cancer example data.
data("breast.example", package="JPSurv")
 
# Subset of observations to use
subset <- "Age_groups == '00-49' & Breast_stage == 'Localized'"

# Fit the unconditional survival join point model
fit <- joinpoint(breast.example, subset,
                 year="Year_of_diagnosis_1975",
                 model.form=NULL, maxnum.jp=0)

# Compute conditional survival S(10 | 5) = P(T>10 | T>5)
ret <- joinpoint.conditional(fit, 5, 10) 

jp.plot.surv(fit, ret, year.col="Year_of_diagnosis_1975")

JPSurv documentation built on June 8, 2025, 12:11 p.m.