JPSurv (version 1.0.1)

joinpoint: Fitting a join point relative survival model

Description

Fitting a joinpoint relative survival model

Usage

joinpoint(formula, data, subset, numJPoints = 0, ...)

Arguments

formula

an object of class "formula": a symbolic description of the model to be fitted. If the input data is from SEER*Stat, the formula can be ~Year. Otherwise, the full formula should be specified as: ~Alive_at_Start + Died + Lost_to_Followup + Expected_Survival_Interval + Interval + Year

data

an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula).

subset

an optional vector specifying a subset of observations to be used in the fitting process.

numJPoints

The maximum number of join points allowed. The default is zero, which is equivalent to a proportional hazard relative survival model.

...

additional arguments to be passed to the low level regression fitting functions.

Value

An object of class "joinpoint" will be returned with attributes:

coefficients

a named vector of coefficients and standard errors

jp

the estimates of the join points

converged

convergence status

predicted

the fitted relative survival rates

xbeta

the linear predictor

ll

log likelihood

aic

AIC

bic

BIC

References

Yu, B., Huang, L., Tiwari, R. C., Feuer, E. J. and Johnson, K. A. (2009), Modeling population-based cancer survival trends by using join point models for grouped survival data. Journal of the Royal Statistical Soceity: Series A, 172, 405-425.

Examples

#load the SEER-9 prostate cancer dataset.
data(prostate);
# Fit the survival join point model with zero join points, i.e., fit the proportional hazard relative survival model.
fit1 = joinpoint(~Year, data=prostate, numJPoints = 0);
# Fit the survival join point model on a subset of the dataset.
fit2 = joinpoint(~Year, data=prostate, Site_and_age_for_total_stage == 18 & Sex == 1, numJPoints = 0);
# Fit the survival join point model for non-SEER*Stat datasets.
fit3 = joinpoint(~Alive_at_Start + Died + Lost_to_Followup + Expected_Survival_Interval
		+ Interval + Year, prostate, numJPoints = 0);
plot(fit1);