survival: Survival Analysis

> library(survival)

バージョン: 2.41.3

関数名 概略
Surv Create a Survival Object
aareg Aalen's additive regression model for censored data
aeqSurv Adjudicate near ties in a Surv object
agreg.fit Cox model fitting functions
aml 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
bladder Bladder Cancer Recurrences
cch Fits proportional hazards regression model to case-cohort data
cgd Chronic Granulotomous Disease data
cgd0 Chronic Granulotomous Disease data
cipoisson Confidence limits for the Poisson
clogit Conditional logistic regression
cluster Identify clusters.
colon Chemotherapy for Stage B/C colon cancer
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 Proportional Hazards Regression Object
coxph.wtest Compute a quadratic form
dsurvreg Distributions available in survreg.
finegray Create data for a Fine-Gray model
flchain Assay of serum free light chain for 7874 subjects.
frailty Random effects terms
genfan Generator fans
heart Stanford Heart Transplant data
is.ratetable Verify that an object is of class ratetable.
kidney Kidney catheter data
lines.survfit Add Lines or Points to a Survival Plot
logLik.coxph logLik method for a Cox model
logan Data from the 1972-78 GSS data used by Logan
lung NCCTG Lung Cancer Data
mgus Monoclonal gammapothy data
mgus2 Monoclonal gammapothy data
model.frame.coxph Model.frame method for coxph objects
model.matrix.coxph Model.matrix method for coxph models
myeloid Acute myeloid leukemia
neardate Find the index of the closest value in data set 2, for each entry in data set one.
nwtco Data from the National Wilm's Tumor Study
ovarian Ovarian Cancer Survival Data
pbc Mayo Clinic Primary Biliary Cirrhosis Data
pbcseq 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
pspline Smoothing splines using a pspline basis
pyears Person Years
quantile.survfit Quantiles from a survfit object
ratetable Ratetable reference in formula
ratetableDate Convert date objects to ratetable form
rats Rat treatment data from Mantel et al
rats2 Rat data from Gail et al.
residuals.coxph Calculate Residuals for a 'coxph' Fit
residuals.survreg Compute Residuals for 'survreg' Objects
retinopathy Diabetic Retinopathy
rhDNase rhDNASE data set
ridge Ridge regression
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 of a Survival Curve
survConcordance Compute a concordance measure.
survSplit Split a survival data set at specified times
survdiff Test Survival Curve Differences
survexp Compute Expected Survival
survexp.fit Compute Expected Survival
survexp.object Expected Survival Curve Object
survexp.us Census Data Sets for the Expected Survival and Person Years Functions
survfit Create survival curves
survfit.coxph 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 Survival Curve Object
survfitcoxph.fit A direct interface to the 'computational engine' of survfit.coxph
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 Parametric Survival Model Object
survregDtest Verify a survreg distribution
tcut Factors for person-year calculations
tmerge Time based merge for survival data
tobin Tobin's Tobit data
transplant Liver transplant waiting list
untangle.specials Help Process the 'specials' Argument of the 'terms' Function.
uspop2 Projected US Population
veteran Veterans' Administration Lung Cancer study

Surv

> Surv(heart$start, heart$stop, heart$event)

  [1] (  0.0,  50.0]  (  0.0,   6.0]  (  0.0,   1.0+] (  1.0,  16.0] 
  [5] (  0.0,  36.0+] ( 36.0,  39.0]  (  0.0,  18.0]  (  0.0,   3.0] 
  [9] (  0.0,  51.0+] ( 51.0, 675.0]  (  0.0,  40.0]  (  0.0,  85.0] 
 [13] (  0.0,  12.0+] ( 12.0,  58.0]  (  0.0,  26.0+] ( 26.0, 153.0] 
 [17] (  0.0,   8.0]  (  0.0,  17.0+] ( 17.0,  81.0]  (  0.0,  37.0+]
 [21] ( 37.0,1387.0]  (  0.0,   1.0]  (  0.0,  28.0+] ( 28.0, 308.0] 
 [25] (  0.0,  36.0]  (  0.0,  20.0+] ( 20.0,  43.0]  (  0.0,  37.0] 
 [29] (  0.0,  18.0+] ( 18.0,  28.0]  (  0.0,   8.0+] (  8.0,1032.0] 
 [33] (  0.0,  12.0+] ( 12.0,  51.0]  (  0.0,   3.0+] (  3.0, 733.0] 
 [37] (  0.0,  83.0+] ( 83.0, 219.0]  (  0.0,  25.0+] ( 25.0,1800.0+]
 [41] (  0.0,1401.0+] (  0.0, 263.0]  (  0.0,  71.0+] ( 71.0,  72.0] 
 [45] (  0.0,  35.0]  (  0.0,  16.0+] ( 16.0, 852.0]  (  0.0,  16.0] 
 [49] (  0.0,  17.0+] ( 17.0,  77.0]  (  0.0,  51.0+] ( 51.0,1587.0+]
 [53] (  0.0,  23.0+] ( 23.0,1572.0+] (  0.0,  12.0]  (  0.0,  46.0+]
 [57] ( 46.0, 100.0]  (  0.0,  19.0+] ( 19.0,  66.0]  (  0.0,   4.5+]
 [61] (  4.5,   5.0]  (  0.0,   2.0+] (  2.0,  53.0]  (  0.0,  41.0+]
 [65] ( 41.0,1408.0+] (  0.0,  58.0+] ( 58.0,1322.0+] (  0.0,   3.0] 
 [69] (  0.0,   2.0]  (  0.0,  40.0]  (  0.0,   1.0+] (  1.0,  45.0] 
 [73] (  0.0,   2.0+] (  2.0, 996.0]  (  0.0,  21.0+] ( 21.0,  72.0] 
 [77] (  0.0,   9.0]  (  0.0,  36.0+] ( 36.0,1142.0+] (  0.0,  83.0+]
 [81] ( 83.0, 980.0]  (  0.0,  32.0+] ( 32.0, 285.0]  (  0.0, 102.0] 
 [85] (  0.0,  41.0+] ( 41.0, 188.0]  (  0.0,   3.0]  (  0.0,  10.0+]
 [89] ( 10.0,  61.0]  (  0.0,  67.0+] ( 67.0, 942.0+] (  0.0, 149.0] 
 [93] (  0.0,  21.0+] ( 21.0, 343.0]  (  0.0,  78.0+] ( 78.0, 916.0+]
 [97] (  0.0,   3.0+] (  3.0,  68.0]  (  0.0,   2.0]  (  0.0,  69.0] 
[101] (  0.0,  27.0+] ( 27.0, 842.0+] (  0.0,  33.0+] ( 33.0, 584.0] 
[105] (  0.0,  12.0+] ( 12.0,  78.0]  (  0.0,  32.0]  (  0.0,  57.0+]
[109] ( 57.0, 285.0]  (  0.0,   3.0+] (  3.0,  68.0]  (  0.0,  10.0+]
[113] ( 10.0, 670.0+] (  0.0,   5.0+] (  5.0,  30.0]  (  0.0,  31.0+]
[117] ( 31.0, 620.0+] (  0.0,   4.0+] (  4.0, 596.0+] (  0.0,  27.0+]
[121] ( 27.0,  90.0]  (  0.0,   5.0+] (  5.0,  17.0]  (  0.0,   2.0] 
[125] (  0.0,  46.0+] ( 46.0, 545.0+] (  0.0,  21.0]  (  0.0, 210.0+]
[129] (210.0, 515.0+] (  0.0,  67.0+] ( 67.0,  96.0]  (  0.0,  26.0+]
[133] ( 26.0, 482.0+] (  0.0,   6.0+] (  6.0, 445.0+] (  0.0, 428.0+]
[137] (  0.0,  32.0+] ( 32.0,  80.0]  (  0.0,  37.0+] ( 37.0, 334.0] 
[141] (  0.0,   5.0]  (  0.0,   8.0+] (  8.0, 397.0+] (  0.0,  60.0+]
[145] ( 60.0, 110.0]  (  0.0,  31.0+] ( 31.0, 370.0+] (  0.0, 139.0+]
[149] (139.0, 207.0]  (  0.0, 160.0+] (160.0, 186.0]  (  0.0, 340.0] 
[153] (  0.0, 310.0+] (310.0, 340.0+] (  0.0,  28.0+] ( 28.0, 265.0+]
[157] (  0.0,   4.0+] (  4.0, 165.0]  (  0.0,   2.0+] (  2.0,  16.0] 
[161] (  0.0,  13.0+] ( 13.0, 180.0+] (  0.0,  21.0+] ( 21.0, 131.0+]
[165] (  0.0,  96.0+] ( 96.0, 109.0+] (  0.0,  21.0]  (  0.0,  38.0+]
[169] ( 38.0,  39.0+] (  0.0,  31.0+] (  0.0,  11.0+] (  0.0,   6.0]

heart

> heart %>% head()

  start stop event             age           year surgery transplant id
1     0   50     1 -17.15537303217 0.123203285421       0          0  1
2     0    6     1   3.83572895277 0.254620123203       0          0  2
3     0    1     0   6.29705681040 0.265571526352       0          0  3
4     1   16     1   6.29705681040 0.265571526352       0          1  3
5     0   36     0  -7.73716632444 0.490075290897       0          0  4
6    36   39     1  -7.73716632444 0.490075290897       0          1  4

coxph

Cox比例ハザードモデル

> test1 <- list(time=c(4,3,1,1,2,2,3), 
+               status=c(1,1,1,0,1,1,0), 
+               x=c(0,2,1,1,1,0,0), 
+               sex=c(0,0,0,0,1,1,1)) 
> coxph(Surv(time, status) ~ x + strata(sex), test1)

Call:
coxph(formula = Surv(time, status) ~ x + strata(sex), data = test1)

      coef exp(coef) se(coef)       z       p
x 0.802318  2.230706 0.822377 0.97561 0.32926

Likelihood ratio test=1.09  on 1 df, p=0.2971171
n= 7, number of events= 5