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
lvcf(): Last Value Carried Forward
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.
nostutter(): Remove repeated events
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(<summary.coxph.penal>): 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.
survfit_confint(): Confidence intervals for survival curves
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(<coxphms>) 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.