Package index • survival

All functions
`Surv()` `is.Surv()`	Create a Survival Object
`Surv2()`	Create a survival object
`Surv2data()`	Convert data from timecourse to (time1,time2) style
`anyDuplicated(<Surv>)` `as.character(<Surv>)` `as.data.frame(<Surv>)` `as.matrix(<Surv>)` `c(<Surv>)` `duplicated(<Surv>)` `format(<Surv>)` `head(<Surv>)` `is.na(<Surv>)` `length(<Surv>)` `mean(<Surv>)` `median(<Surv>)` `names(<Surv>)` `names<-`(<Surv>) `quantile(<Surv>)` `plot(<Surv>)` `rep(<Surv>)` `rep.int(<Surv>)` `rep_len(<Surv>)` `rev(<Surv>)` `t(<Surv>)` `tail(<Surv>)` `unique(<Surv>)`	Methods for Surv objects
`aareg()`	Aalen's additive regression model for censored data
`aeqSurv()`	Adjudicate near ties in a Surv object
`aggregate(<survfit>)`	Average survival curves
`agreg.fit()` `coxph.fit()`	Cox model fitting functions
`aml` `leukemia` `cancer`	Acute Myelogenous Leukemia survival data
`anova(<coxph>)`	Analysis of Deviance for a Cox model.
`attrassign()`	Create new-style "assign" attribute
`basehaz()`	Alias for the survfit function
`bladder1` `bladder` `bladder2` `cancer`	Bladder Cancer Recurrences
`blogit()` `bprobit()` `bcloglog()` `blog()`	Bounded link functions
`brier()`	Compute the Brier score for a Cox model
`cch()`	Fits proportional hazards regression model to case-cohort data
`cgd`	Chronic Granulotamous Disease data
`cgd0`	Chronic Granulotomous Disease data
`cipoisson()`	Confidence limits for the Poisson
`clogit()`	Conditional logistic regression
`cluster()`	Identify clusters.
`colon` `cancer`	Chemotherapy for Stage B/C colon cancer
`concordance()`	Compute the concordance statistic for data or a model
`concordancefit()`	Compute the concordance
`cox.zph()`	Test the Proportional Hazards Assumption of a Cox Regression
`coxph()`	Fit Proportional Hazards Regression Model
`coxph.control()`	Ancillary arguments for controlling coxph fits
`coxph.detail()`	Details of a Cox Model Fit
`coxph.object` `extractAIC.coxph.penal` `print.coxph`	Proportional Hazards Regression Object
`coxph.wtest()`	Compute a quadratic form
`coxphms.object`	Multi-state Proportional Hazards Regression Object
`coxsurv.fit()`	A direct interface to the `computational engine' of survfit.coxph
`diabetic`	Ddiabetic retinopathy
`dsurvreg()` `psurvreg()` `qsurvreg()` `rsurvreg()`	Distributions available in survreg.
`finegray()`	Create data for a Fine-Gray model
`flchain`	Assay of serum free light chain for 7874 subjects.
`frailty()` `frailty.gamma()` `frailty.gaussian()` `frailty.t()`	Random effects terms
`gbsg` `cancer`	Breast cancer data sets used in Royston and Altman (2013)
`heart`	Stanford Heart Transplant data
`cancer`	Mouse cancer data
`is.ratetable()`	Verify that an object is of class ratetable.
`kidney` `cancer`	Kidney catheter data
`levels(<Surv>)`	Return the states of a multi-state Surv object
`lines(<survfit>)` `lines(<survexp>)` `points(<survfit>)`	Add Lines or Points to a Survival Plot
`logLik(<coxph>)` `logLik(<survreg>)`	logLik method for a Cox model
`logan`	Data from the 1972-78 GSS data used by Logan
`lung` `cancer`	NCCTG Lung Cancer Data
`mgus` `mgus1` `cancer`	Monoclonal gammopathy data
`mgus2` `cancer`	Monoclonal gammopathy data
`model.frame(<coxph>)`	Model.frame method for coxph objects
`model.matrix(<coxph>)`	Model.matrix method for coxph models
`myeloid` `cancer`	Acute myeloid leukemia
`myeloma` `cancer`	Survival times of patients with multiple myeloma
`nafld1` `nafld2` `nafld3` `nafld`	Non-alcoholic fatty liver disease
`neardate()`	Find the index of the closest value in data set 2, for each entry in data set one.
`nsk()`	Natural splines with knot heights as the basis.
`nwtco`	Data from the National Wilm's Tumor Study
`ovarian` `cancer`	Ovarian Cancer Survival Data
`pbc`	Mayo Clinic Primary Biliary Cholangitis Data
`pbcseq` `pbc`	Mayo Clinic Primary Biliary Cirrhosis, sequential data
`plot(<aareg>)`	Plot an aareg object.
`plot(<cox.zph>)`	Graphical Test of Proportional Hazards
`plot(<survfit>)`	Plot method for `survfit` objects
`predict(<coxph>)`	Predictions for a Cox model
`predict(<survreg>)`	Predicted Values for a `survreg' Object
`print(<aareg>)`	Print an aareg object
`print(<summary.coxph>)`	Print method for summary.coxph objects
`print(<summary.survexp>)`	Print Survexp Summary
`print(<summary.survfit>)`	Print Survfit Summary
`print(<survfit>)`	Print a Short Summary of a Survival Curve
`pseudo()`	Pseudo values for survival.
`pspline()` `psplineinverse()`	Smoothing splines using a pspline basis
`pyears()`	Person Years
`quantile(<survfit>)` `quantile(<survfitms>)` `median(<survfit>)`	Quantiles from a survfit object
`ratetable()`	Allow ratetable() terms in a model
`ratetableDate()`	Convert date objects to ratetable form
`rats` `cancer`	Rat treatment data from Mantel et al
`rats2` `cancer`	Rat data from Gail et al.
`reliability`	Reliability data sets
`residuals(<coxph>)` `residuals(<coxphms>)` `residuals(<coxph.null>)`	Calculate Residuals for a `coxph' Fit
`residuals(<survfit>)`	IJ residuals from a survfit object.
`residuals(<survreg>)`	Compute Residuals for `survreg' Objects
`retinopathy`	Diabetic Retinopathy
`rhDNase`	rhDNASE data set
`ridge()`	Ridge regression
`rotterdam` `cancer`	Breast cancer data set used in Royston and Altman (2013)
`royston()`	Compute Royston's D for a Cox model
`rttright()`	Compute redistribute-to-the-right weights
`solder`	Data from a soldering experiment
`stanford2`	More Stanford Heart Transplant data
`statefig()`	Draw a state space figure.
`strata()`	Identify Stratification Variables
`summary(<aareg>)`	Summarize an aareg fit
`summary(<coxph>)`	Summary method for Cox models
`summary(<pyears>)`	Summary function for pyears objecs
`summary(<survexp>)`	Summary function for a survexp object
`summary(<survfit>)` `summary(<survfitms>)`	Summary of a Survival Curve
`survSplit()`	Split a survival data set at specified times
`survcheck()`	Checks of a survival data set
`survcondense()`	Shorten a (time1, time2) survival dataset
`survdiff()`	Test Survival Curve Differences
`survexp()`	Compute Expected Survival
`survexp.fit()`	Compute Expected Survival
`survexp.object`	Expected Survival Curve Object
`survexp`	Census Data Sets for the Expected Survival and Person Years Functions
`survfit()`	Create survival curves
`survfit(<coxph>)` `survfit(<coxphms>)`	Compute a Survival Curve from a Cox model
`survfit(<formula>)`	Compute a Survival Curve for Censored Data
`survfit(<matrix>)`	Create Aalen-Johansen estimates of multi-state survival from a matrix of hazards.
`survfit.object` `survfitms.object`	Survival Curve Object
`survfit0()`	Convert the format of a survfit object.
`survfitcoxph.fit()`	A direct interface to the `computational engine' of survfit.coxph
`survConcordance()` `survConcordance.fit()`	Deprecated functions in package survival
`survobrien()`	O'Brien's Test for Association of a Single Variable with Survival
`survreg()`	Regression for a Parametric Survival Model
`survreg.control()`	Package options for survreg and coxph
`survreg.distributions`	Parametric Survival Distributions
`survreg.object` `print.survreg` `summary.survreg`	Parametric Survival Model Object
`survregDtest()`	Verify a survreg distribution
`tcut()` `levels(<tcut>)`	Factors for person-year calculations
`totimeline()` `fromtimeline()`	Convert to/from a timeline data set format
`tmerge()`	Time based merge for survival data
`tobin`	Tobin's Tobit data
`transplant`	Liver transplant waiting list
`udca` `udca2`	Data from a trial of usrodeoxycholic acid
`untangle.specials()`	Help Process the `specials' Argument of the `terms' Function.
`uspop2`	Projected US Population
`vcov(<coxph>)` `vcov(<survreg>)`	Variance-covariance matrix
`veteran` `cancer`	Veterans' Administration Lung Cancer study
`xtfrm(<Surv>)`	Sorting order for Surv objects
`yates()`	Population prediction
`yates_setup()`	Method for adding new models to the `yates` function.

Reference

All functions