joinpoint: Fitting a join point relative survival model

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

Fitting a join point relative survival model

Description

Fitting a joinpoint relative survival model

Usage

joinpoint(data, subset=NULL, na.action = na.fail, 
	year="Year", interval="Interval",
	number.event="Died", number.alive="Alive_at_Start", 
       number.loss="Lost_to_Followup",
	expected.rate="Expected_Survival_Interval", observedrelsurv = NULL,
	model.form = NULL, maxnum.jp = 0, proj.year.num=5,
	op=list(),
	delLastIntvl=FALSE, add.data.cols="_ALL_")

Arguments

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 string specifying a subset of observations to be used in the fitting process.
na.action	how NAs are treated. The default is first, any na.action attribute of data, second a na.action setting of options, and third na.fail if that is unset. The "factory-fresh" default is na.omit. Another possible value is NULL. The default is na.fail
year	It is about the year or time values and could be a vector of numeric or a character string giving a column name of the argument 'data'. The default is the string 'Year'.
interval	It is about the time elapsed from start to the event and could be a vector of numeric or a character string giving a column name of the argument 'data'. The default is the string 'Interval'.
number.event	It is the number of events or died and could be a vector of numeric or a character string giving a column name of the argument 'data'. The default is the string 'Died'.
number.alive	It is about the number of alive and could be a vector of numeric or a character string giving a column name of the argument 'data'. The default is the string 'Alive_at_Start'.
number.loss	It is about the number of Lost_to_Followup and could be a vector of numeric or a character string giving a column name of the argument 'data'. The default is the string 'Lost_to_Followup'.
expected.rate	It is about the interval expected survival and could be a vector of numeric or a character string giving a column name of the argument 'data'. The default is the string 'Expected_Survival_Interval'. If this column does not exist, then a column of ones will be created for expected.rate.
observedrelsurv	It is about the observed cumulative relative survival and could be a vector of numeric or a character string giving a column name of the argument 'data'. If NULL, then no observed values. The default is NULL.
model.form	an object of class "formula": a symbolic description of covariates. Example: ~-1+age+as.factor(stage)
maxnum.jp	The maximum number of join points allowed. The default is zero, which is equivalent to a proportional hazard relative survival model.
proj.year.num	The number of projection years for use in the prediction step. Default value is 5 years, with a valid range of 0 to 30 years.
op	List of more options. Details — numbetwn: integer value, number of skipped obs between joinpoints exclusive (not count for the joinpoints). Default is 2. numfromstart: integer value, number of skipped obs from the first obs to joinpoints exclusive (not count for the joinpoint). Default is 3. numtoend: integer value, number of skipped obs from the first obs to joinpoints exclusive (not count for the joinpoint). Default is 4.
delLastIntvl	an logical value indicating whether or not deleting records of last intervals of all years. The default is false.
add.data.cols	Character vector of column names in data to add onto the returned data frames of results. Use "_ALL_" to add all columns and use NULL to not add any columns. The default is "_ALL_".

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
fullpredicted	the full output matrix, with all year/interval combinations and projections
xbeta	the linear predictor
ll	log likelihood
aic	AIC
bic	BIC
FitList	a list that contains fitting results for the number of joinpoints = 0,1,...,numJPoints respectively.

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 Society: Series A, 172, 405-425.

Examples

#Load the provided SEER 18 breast cancer example data.
data("breast.example", package="JPSurv")

subsetStr="Year_of_diagnosis_1975 >= 1975 & Age_groups == '00-49' & Breast_stage == 'Localized'"
# Fit the survival join point model with zero join points, 
#  i.e., fit the proportional hazard relative survival model.
fit = joinpoint(data=breast.example,
                 subset = subsetStr,
                 year="Year_of_diagnosis_1975",
                 observedrelsurv="Relative_Survival_Cum",
                 model.form = NULL,
                 maxnum.jp = 0)

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