R (język programowania)/Analiza przeżyć
Analiza przeżyć ( ang. Survival analysis)[1]
Pakiety
[edytuj]- survival = podstawowy pakiet
- KMsurv = dodatkowe materiały z książki Klein and Moeschberger : "Survival Analysis, Techniques for Censored and Truncated Data", Springer (1997)
- funkcja ggsurv [2]
- OIsurv = dodatkowe materiału ze strony www.openintro.org
- survMisc [3][4]
survival
[edytuj]Ładujemy biblkiotekę [5]
library(survival) #
Sprawdzamy :
library(help=survival) # see the version number, list of available functions and data sets.
Przykładowy wynik :
Informacja dotycząca pakietu ‘survival’
Opis:
Title: Survival Analysis
Maintainer: Terry Therneau <therneau.terry@mayo.edu>
Priority: recommended
Package: survival
Version: 2.37-4
Date: 2013-02-26
Depends: stats, utils, graphics, splines, R (>= 2.13.0)
LazyData: Yes
LazyLoad: Yes
ByteCompile: Yes
Authors@R: c(person(c("Terry", "M"), "Therneau",
email="therneau.terry@mayo.edu", role=c("aut",
"cre")), person("Lumley", "Thomas", role=c("ctb",
"trl"), comment="original S->R port and maintainer
until 2009"))
Author: Terry Therneau
Description: survival analysis: descriptive statistics,
two-sample tests, parametric accelerated failure
models, Cox model. Delayed entry (truncation)
allowed for all models; interval censoring for
parametric models. Case-cohort designs.
License: LGPL (>= 2)
URL: http://r-forge.r-project.org
Packaged: 2013-02-26 17:19:25 UTC; therneau
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2013-02-26 19:03:03
Built: R 3.0.0; x86_64-pc-linux-gnu; 2013-04-29 18:21:29
UTC; unix
Indeks:
Surv Create a Survival Object
aareg Aalen's additive regression model for censored
data
aml Acute Myelogenous Leukemia survival data
anova.coxph Analysis of Deviance for a Cox model.
attrassign Create new-style "assign" attribute
basehaz Compute the baseline survival curve for a Cox
model
bladder Bladder Cancer Recurrences
cch Fits proportional hazards regression model to
case-cohort data
cgd Chronic Granulotomous Disease data
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 controling coxph fits
coxph.detail Details of a Cox Model Fit
coxph.object Proportional Hazards Regression Object
dsurvreg Distributions available in survreg.
frailty Random effects terms
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
logan Data from the 1972-78 GSS data used by Logan
lung NCCTG Lung Cancer Data
mgus Monoclonal gammapothy data
model.frame.coxph Model.frame method for coxph objects
model.matrix.coxph Model.matrix method for coxph models
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
ridge Ridge regression
stanford2 More Stanford Heart Transplant data
strata Identify Stratification Variables
summary.aareg Summarize an aareg fit
summary.coxph Summary method for Cox models
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.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.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
tobin Tobin's Tobit data
tt Mark time tranform terms
untangle.specials Help Process the 'specials' Argument of the
'terms' Function.
uspop2 Projected US Population
veteran Veterans' Administration Lung Cancer study
Dalsza informacja jest dostępna w następujących ilustracjach w katalogu
‘/usr/lib/R/library/survival/doc’:
timedep: Using Time Dependent Covariates (source, pdf)
Pamiętaj o wyjściu za pomocą
:q
Funkcje
[edytuj]Najważniejsze funkcja :
- Surv ( Survival object = the data has to be in the proper format )
- survfit ( Kaplan-Meier estimates )[6]
- survdiff (The log-rank test )
- coxph (The Cox proportional hazards model )
- survreg (The Accelerated failure time model )
Surv {survival}
[edytuj]Surv (czas, zdarzenie)
gdzie : [7]
- czas (ang. follow-up time) to zmienna reprezentująca długość czasu obserwacji obiektów
- wydarzenie( ang. event status indicator) to zmienna logiczna ( zero-jedynkowa, binarna, nie/tak, 0/1) określająca, czy dla danego obiektu ze zbioru danych wystąpiło w okresie obserwacji badane zdarzenie;
dane
[edytuj]Jak przygotować dane ? [8]
aml
[edytuj]Ładujemy dane aml
data(aml)
w nowszych wersjach pakietu otrzymujemy błąd :
Komunikat ostrzegawczy: In data(aml) : zbiór danych ‘aml’ nie został znaleziony
pomimo że dane są w pakiecie. Jest spowodowane użyciem lazyData[9]. Sprawdzamy :
exists('aml')
przykładowy wynik :
[1] TRUE
wczytujemy i oglądamy dane :
aml
wynik :
time status x 1 9 1 Maintained 2 13 1 Maintained 3 13 0 Maintained 4 18 1 Maintained 5 23 1 Maintained 6 28 0 Maintained 7 31 1 Maintained 8 34 1 Maintained 9 45 0 Maintained 10 48 1 Maintained 11 161 0 Maintained 12 5 1 Nonmaintained 13 5 1 Nonmaintained 14 8 1 Nonmaintained 15 8 1 Nonmaintained 16 12 1 Nonmaintained 17 16 0 Nonmaintained 18 23 1 Nonmaintained 19 27 1 Nonmaintained 20 30 1 Nonmaintained 21 33 1 Nonmaintained 22 43 1 Nonmaintained 23 45 1 Nonmaintained
Wykresy
[edytuj]Wykres Kaplan-Meier : [10]
fit <- survfit(Surv(time, status) ~ x, data = aml)
plot(fit, lty = 2:3)
legend(100, .8, c("Maintained", "Nonmaintained"), lty = 2:3)
library(survival)
time = c(1, 12, 22, 29, 31, 36, 38, 50, 60, 61, 70, 88, 99, 110, 140)
event = c(0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0)
fit = survfit( Surv(time, event)~1 )
plot(fit, main="Estymator Kaplane-Meiera", xlab="t = Czas ( dni)", ylab="S(t) = Prawdopodobieństwo")
Przykłady:
Źródła
[edytuj]- ↑ Analiza przeżycia w wikipedii
- ↑ Creating good looking survival curves – the 'ggsurv' function by Edwin Thoen
- ↑ survMisc
- ↑ Plotting survival curves in R with ggplot2
- ↑ Use Software R to do Survival Analysis and Simulation by Mai Zhou
- ↑ Compute a Survival Curve for Censored Data
- ↑ Survival Analysis - analiza przeżyć. Statystyka Medyczna : Branicka, Pękalski
- ↑ How to Make Survival Analysis Variables in R by Monika Wahi
- ↑ Loading data from a program
- ↑ survfit.formula {survival}
- ↑ Drawing survival curves in R
- ↑ How to Plot a Survival Curve (or Two) in R by Monika Wahi