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);
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(JPSurv)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/JPSurv/joinpoint.Rd_%03d_medium.png", width=480, height=480)
> ### Name: joinpoint
> ### Title: Fitting a join point relative survival model
> ### Aliases: joinpoint print.joinpoint plot.joinpoint summary.joinpoint
>
> ### ** 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);
>
>
>
>
>
> dev.off()
null device
1
>