survexp(survival)
survexp()所属R语言包：survival
Compute Expected Survival
计算预期生存
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Returns either the expected survival of a cohort of subjects, or the individual expected survival for each subject.
返回一个科目的队列，或个人预计每个科目的生存预期生存。
用法----------Usage----------
survexp(formula, data, weights, subset, na.action, rmap, times, cohort=TRUE,
conditional=FALSE, ratetable=survexp.us, scale=1, npoints,
se.fit, model=FALSE, x=FALSE, y=FALSE)
参数----------Arguments----------
参数：formula
formula object. The response variable is a vector of follow-up times and is optional. The predictors consist of optional grouping variables separated by the + operator (as in survfit), and is often ~1, i.e., expected survival for the entire group.
公式对象。响应变量是一个随访时间的向量，是可选的。预测包括分开+运营商（survfit），往往是~1，即，预计整个集团的生存作为可选的分组变量。
参数：data
data frame in which to interpret the variables named in the formula, subset and weights arguments.
数据框在解释formula名为变量，subset和weights参数。
参数：weights
case weights.
的情况下重量。
参数：subset
expression indicating a subset of the rows of data to be used in the fit.
表达指示data要适合使用的行的一个子集。
参数：na.action
function to filter missing data. This is applied to the model frame after subset has been applied. Default is options()$na.action. A possible value for na.action is na.omit, which deletes observations that contain one or more missing values.
函数来过滤丢失的数据。这是适用于后subset已应用于模型框架。默认options()$na.action。一个可能值na.action的na.omit，删除包含一个或多个缺失值的观测。
参数：rmap
an optional list that maps data set names to the ratetable names. See the details section below.
一个可选列表，地图数据设置的ratetable名称命名。见下面的细节部分。
参数：times
vector of follow-up times at which the resulting survival curve is evaluated. If absent, the result will be reported for each unique value of the vector of follow-up times supplied in formula.
向量的后续造成的生存曲线进行评估的时间。如果缺席，结果将报告为每个独特的价值在formula提供后续的向量。
参数：cohort
logical value: if FALSE, each subject is treated as a subgroup of size 1. The default is TRUE.
逻辑值：如果FALSE，每个主题作为一个分组大小为1处理。默认TRUE。
参数：conditional
logical value: if TRUE, the follow-up times supplied in formula are death times and conditional expected survival is computed. If FALSE, the follow-up times are potential censoring times. If follow-up times are missing in formula, this argument is ignored.
逻辑值：如果TRUE，formula死亡时间和计算条件的预期生存提供后续倍。如果FALSE，随访时间是潜在的审查倍。如果随访时间在formula失踪，则忽略此参数。
参数：ratetable
a table of event rates, such as survexp.uswhite, or a fitted Cox model.
一个事件的发生率，如survexp.uswhite，或拟合Cox模型表。
参数：scale
numeric value to scale the results. If ratetable is in units/day, scale = 365.25 causes the output to be reported in years.
数值扩展的结果。 ratetable如果/天，scale = 365.25导致输出报告将在几年的单位。
参数：npoints
number of points at which to calculate intermediate results, evenly spaced over the range of the follow-up times. The usual (exact) calculation is done at each unique follow-up time. For very large data sets specifying npoints can reduce the amount of memory and computation required. For a prediction from a Cox model npoints is ignored.
点的数量来计算的中间结果，平均随访时间范围内间隔。通常的（确切）进行计算，在每一个独特的随访时间。对于非常大的数据集指定npoints可以减少所需的内存和计算量。对于一个从Cox模型npoints预测被忽略。
参数：se.fit
compute the standard error of the predicted survival. The default is to compute standard errors whenever possible, which at this time is only for the Ederer method and a Cox model as the rate table.
计算标准错误的预测生存。默认为计算标准误差，只要有可能，此时只有埃德雷尔方法和费率表的Cox模型。
参数：model,x,y
flags to control what is returned. If any of these is true, then the model frame, the model matrix, and/or the vector of response times will be returned as components of the final result, with the same names as the flag arguments. </table>
标志来控制返回。如果这些是真的，那么返回的框架模型，该模型矩阵，和/或响应时间的向量将作为最终结果的组成部分，作为标志参数相同的名称。 </ TABLE>
Details
详情----------Details----------
Individual expected survival is usually used in models or testing, to "correct" for the age and sex composition of a group of subjects. For instance, assume that birth date, entry date into the study, sex and actual survival time are all known for a group of subjects. The survexp.us population tables contain expected death rates based on calendar year, sex and age. Then
个人预期生存期通常用于模型或测试，一组受试者的年龄和性别组成的“纠正”。例如，假设投入到学习中，出生日期，入境日期，性别和所有已知的实际存活时间为一组科目。 survexp.us人口表包含预期的日历年度，性别和年龄上的死亡率。然后
值----------Value----------
if cohort=TRUE an object of class survexp, otherwise a vector of per-subject expected survival values. The former contains the number of subjects at risk and the expected survival for the cohort at each requested time.
如果cohort=TRUE类survexp，否则矢量每学科的生存价值的对象。前者包含的风险科目的数量和队列在每个请求的时间预计生存。
参考文献----------References----------
Biometrics, 39:173-84.
The relative survival rate: a statistical methodology. Natl Cancer Inst Monogr, 6:101-21.
Cancer survival corrected for heterogeneity in patient withdrawal. Biometrics, 38:933-942.
Background mortality in clinical survival studies. Lancet, 341: 872-875.
参见----------See Also----------
survfit, pyears, survexp.us, survexp.fit.
survfit，pyears，survexp.us，survexp.fit。
举例----------Examples----------
# []
# Stanford heart transplant data[斯坦福大学心脏移植数据]
# We don't have sex in the data set, but know it to be nearly all males.[我们并没有在数据集的性别，但知道这是几乎所有男性。]
# Estimate of conditional survival [有条件的生存的估计]
survexp(futime ~ 1, rmap=list(sex="male", year=accept.dt,
age=(accept.dt-birth.dt)), conditional=TRUE, data=jasa)
# Estimate of expected survival stratified by prior surgery [预计生存分层估计前手术]
survexp(futime ~ surgery, rmap= list(sex="male", year=accept.dt,
age=(accept.dt-birth.dt)), conditional=TRUE, data=jasa)
## Compare the survival curves for the Mayo PBC data to Cox model fit[＃Cox模型拟合比较为梅奥中国人民银行数据的生存曲线]
## [＃]
pfit <-coxph(Surv(time,status>0) ~ trt + log(bili) + log(protime) + age +
platelet, data=pbc)
plot(survfit(Surv(time, status>0) ~ trt, data=pbc))
lines(survexp( ~ trt, ratetable=pfit, data=pbc), col='purple')
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。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-17 10:11:18
