survest.psm(rms)
survest.psm()所属R语言包：rms
Parametric Survival Estimates
参数生存率估计值
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes predicted survival probabilities or hazards and optionally confidence limits (for survival only) for parametric survival models fitted with psm. If getting predictions for more than one observation, times must be specified. For a model without predictors, no input data are specified.
计算预测的生存概率或危害，并可选配备psm参数生存模型的置信区间（只为生存）。如果得到预测为一个以上的观察，times必须被指定。对于模型没有预测，没有输入数据被指定。
用法----------Usage----------
## S3 method for class 'psm'
survest(fit, newdata, linear.predictors, x, times, fun,
loglog=FALSE, conf.int=0.95,
what=c("survival","hazard","parallel"), ...)
## S3 method for class 'survest.psm'
print(x, ...)
参数----------Arguments----------
参数：fit
fit from psm
适合从psm
参数：newdata, linear.predictors, x, times, conf.int
see survest.cph. One of newdata, linear.predictors, x must be given. linear.predictors includes the intercept. If times is omitted, predictions are made at 200 equally spaced points between 0 and the maximum failure/censoring time used to fit the model. x can also be a result from survest.psm.
看到survest.cph。之一newdata，linear.predictors，x必须给予。 linear.predictors包括拦截。 times如果被省略，200之间的等距点，最大的失败/审查所用的时间，以适应模型进行预测。 x也可以从survest.psm的结果。
参数：what
The default is to compute survival probabilities. Set what="hazard" or some abbreviation of "hazard" to compute hazard rates. what="parallel" assumes that the length of times is the number of subjects (or one), and causes survest to estimate the i^{th} subject's survival probability at the i^{th} value of times (or at the scalar value of times). what="parallel" is used by val.surv for example.
默认值是计算生存概率。设置what="hazard"或"hazard"计算风险率的缩写。 what="parallel"假设times的长度是多少的主题（或一个），并导致survest估计的i^{th}主题的生存概率在i^{th}值的times（或的标量值times）。 what="parallel"使用val.surv的例子。
参数：loglog
set to TRUE to transform survival estimates and confidence limits using log-log
设置为TRUE改造生存率估计和置信限使用log记录
参数：fun
a function to transform estimates and optional confidence intervals
一个函数来变换估计和可选的置信区间
参数：...
unused
未使用的
Details
详细信息----------Details----------
Confidence intervals are based on asymptotic normality of the linear predictors. The intervals account for the fact that a scale parameter may have been estimated jointly with beta.
置信区间是基于线性预测的渐近正态性。的时间间隔为尺度参数估计与β共同帐户。
值----------Value----------
see survest.cph. If the model has no predictors, predictions are made with respect to varying time only, and the returned object is of class "survfit" so the survival curve can be plotted with survplot.survfit. If times is omitted, the entire survival curve or hazard from t=0,...,fit$maxtime is estimated, with increments computed to yield 200 points where fit$maxtime is the maximum survival time in the data used in model fitting. Otherwise, the times vector controls the time points used.
看到survest.cph。如果模型没有预测，预测是由不同的时间只有返回的对象的类"survfit"“这样的生存曲线可以绘制与survplot.survfit。如果times省略，整个生存曲线或危险t=0,...,fit$maxtime估计，增量计算得到200分，其中fit$maxtime是所使用的数据模型拟合的最大生存时间。否则，times矢量控制的时间点。
（作者）----------Author(s)----------
Frank Harrell<br>
Department of Biostatistics<br>
Vanderbilt University<br>
f.harrell@vanderbilt.edu
参见----------See Also----------
psm, survreg, rms, survfit, predictrms, survplot, survreg.distributions
psm，survreg，rms，survfit，predictrms，survplot，survreg.distributions
实例----------Examples----------
# Simulate data from a proportional hazards population model[从人口比例风险模型的模拟数据]
n <- 1000
set.seed(731)
age <- 50 + 12*rnorm(n)
label(age) <- "Age"
cens <- 15*runif(n)
h <- .02*exp(.04*(age-50))
dt <- -log(runif(n))/h
label(dt) <- 'Follow-up Time'
e <- ifelse(dt <= cens,1,0)
dt <- pmin(dt, cens)
units(dt) <- "Year"
S <- Surv(dt,e)
f <- psm(S ~ lsp(age,c(40,70)))
survest(f, data.frame(age=seq(20,80,by=5)), times=2)
#Get predicted survival curve for 40 year old[预测生存曲线40岁]
survest(f, data.frame(age=40))
#Get hazard function for 40 year old[风险函数为40岁]
survest(f, data.frame(age=40), what="hazard")$surv #still called surv[仍然被称为存活率]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
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发表于 2012-9-27 19:16:29
