cch(survival)
cch()所属R语言包：survival
Fits proportional hazards regression model to case-cohort data
符合比例风险回归模型的情况下，队列数据
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Returns estimates and standard errors from relative risk regression fit to data from case-cohort studies. A choice is available among the Prentice, Self-Prentice and Lin-Ying methods for unstratified data. For stratified data the choice is between Borgan I, a generalization of the Self-Prentice estimator for unstratified case-cohort data, and Borgan II, a generalization of the Lin-Ying estimator.
回报估计标准误差和相对风险回归适合病例队列研究的数据。不分层数据的徒弟，自徒弟，林英法之间的选择。对于分层数据的选择是自徒弟估计不分层的情况下，队列数据的概括，我Borgan，Borgan二，林英估计的推广。
用法----------Usage----------
cch(formula, data = sys.parent(), subcoh, id, stratum=NULL, cohort.size,
method =c(" rentice","SelfPrentice","LinYing","I.Borgan","II.Borgan"),
robust=FALSE)
参数----------Arguments----------
参数：formula
A formula object that must have a Surv object as the response. The Surv object must be of type "right", or of type "counting".
公式对象，必须有一个Surv作为响应的对象。幸存者的对象必须是类型"right"，或类型"counting"。
参数：subcoh
Vector of indicatorsfor subjects sampled as part of the sub-cohort. Code 1 or TRUE for members of the sub-cohort, 0 or FALSE for others. If data is a data frame then subcoh may be a one-sided formula.
indicatorsfor科目的矢量采样子队列的一部分。代码1或TRUE子队列的成员，0或FALSE为他人。 data如果是一个数据框，那么subcoh可能是一种片面的公式。
参数：id
Vector of unique identifiers, or formula specifying such a vector.
向量的唯一标识符，或指定一个向量公式。
参数：stratum
A vector of stratum indicators or a formula specifying such a vector
一个阶层指标的向量，或指定一个向量公式
参数：cohort.size
Vector with size of each stratum original cohort from which subcohort was sampled
向量与各阶层从原来的队列subcohort采样大小
参数：data
An optional data frame in which to interpret the variables occurring in the formula.
解释发生在公式中的变量的一个可选的数据框。
参数：method
Three procedures are available. The default method is "rentice", with options for "SelfPrentice" or "LinYing".
三个程序是可用的。默认的方法是“徒弟”，“SelfPrentice”或“临颍”选项。
参数：robust
For "LinYing" only, if robust=TRUE, use design-based standard errors even for phase I
"LinYing"，如果robust=TRUE，使用基于设计标准的错误甚至第一阶段
Details
详情----------Details----------
Implements methods for case-cohort data analysis described by Therneau and Li (1999). The three methods differ in the choice of "risk sets" used to compare the covariate values of the failure with those of others at risk at the time of failure. "rentice" uses the sub-cohort members "at risk" plus the failure if that occurs outside the sub-cohort and is score unbiased. "SelfPren" (Self-Prentice) uses just the sub-cohort members "at risk". These two have the same asymptotic variance-covariance matrix. "LinYing" (Lin-Ying) uses the all members of the sub-cohort and all failures outside the sub-cohort who are "at risk". The methods also differ in the weights given to different score contributions.
实现由Therneau和李（1999）所述的情况下，队列数据分析的方法。这三种方法不同，选择协变量的值与其他危险的失败，在失败的时候比较“风险套”。使用“徒弟”，“危险”的子队列成员加上失败，如果发生这种情况以外的子队列和得分持平。 “SelfPren”（自徒弟）使用子世代“危险”的成员。这两个有相同的渐近方差 - 协方差矩阵。 “临颍”（林莹）使用子队列，谁是“危险”外的子队列的所有成员和所有的失败。该方法也不同，给予不同的得分贡献的权重。
The data argument must not have missing values for any variables in the model. There must not be any censored observations outside the subcohort.
data参数不能有遗漏值模型中的任何变量。不能有外subcohort任何审查意见。
值----------Value----------
An object of class "cch" incorporating a list of estimated regression coefficients and two estimates of their asymptotic variance-covariance matrix.
一个类对象纳入“CCH”的估计回归系数估计的渐近方差 - 协方差矩阵列表。
参数：coef
regression coefficients.
回归系数。
参数：naive.var
Self-Prentice model based variance-covariance matrix.
自徒弟基于模型的协方差矩阵。
参数：var
Lin-Ying empirical variance-covariance matrix. </table>
林莹经验的协方差矩阵。 </ TABLE>
作者（S）----------Author(s)----------
Norman Breslow, modified by Thomas Lumley
参考文献----------References----------
disease prevention trials. Biometrika 73: 1–11.
results for case-cohort studies. Annals of Statistics 16: 64–81.
Journal of the American Statistical Association 88: 1341–1349.
50: 1064–1072
Lifetime Data Analysis 5: 99–112.
Exposure stratified case-cohort designs. Lifetime Data Analysis 6, 39-58.
参见----------See Also----------
twophase and svycoxph in the "survey" package for more general two-phase designs. http://faculty.washington.edu/tlumley/survey/
twophase和svycoxph在“调查”更一般的两相设计方案。 http://faculty.washington.edu/tlumley/survey/~~V
举例----------Examples----------
## The complete Wilms Tumor Data [＃完整的肾母单元瘤数据]
## (Breslow and Chatterjee, Applied Statistics, 1999)[＃（布瑞斯罗夫和查特吉，应用统计，1999年）]
## subcohort selected by simple random sampling.[＃subcohort简单随机抽样选择。]
##[＃]
subcoh <- nwtco$in.subcohort
selccoh <- with(nwtco, rel==1|subcoh==1)
ccoh.data <- nwtco[selccoh,]
ccoh.data$subcohort <- subcoh[selccoh]
## central-lab histology [＃中央组织学实验室]
ccoh.data$histol <- factor(ccoh.data$histol,labels=c("FH","UH"))
## tumour stage[＃肿瘤分期]
ccoh.data$stage <- factor(ccoh.data$stage,labels=c("I","II","III","IV"))
ccoh.data$age <- ccoh.data$age/12 # Age in years[在多年的年龄]
##[＃]
## Standard case-cohort analysis: simple random subcohort [＃标准的情况下，队列分析：简单随机subcohort]
##[＃]
fit.ccP <- cch(Surv(edrel, rel) ~ stage + histol + age, data =ccoh.data,
subcoh = ~subcohort, id=~seqno, cohort.size=4028)
fit.ccP
fit.ccSP <- cch(Surv(edrel, rel) ~ stage + histol + age, data =ccoh.data,
subcoh = ~subcohort, id=~seqno, cohort.size=4028, method="SelfPren")
summary(fit.ccSP)
##[＃]
## (post-)stratified on instit[＃（后）分层instit]
##[＃]
stratsizes<-table(nwtco$instit)
fit.BI<- cch(Surv(edrel, rel) ~ stage + histol + age, data =ccoh.data,
subcoh = ~subcohort, id=~seqno, stratum=~instit, cohort.size=stratsizes,
method="I.Borgan")
summary(fit.BI)
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 2012-2-17 09:46:31
