Description Usage Arguments Value References Examples
Fitting a joinpoint relative survival model
1 |
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. |
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 |
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.
1 2 3 4 5 6 7 8 9 10 | #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);
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