simexaft(simexaft)
simexaft()所属R语言包：simexaft
SIMEX Algorithm for Accelerated Failure Time Model with Covariates Subject to Measurement Error
SIMEX加速失效时间模型与算法协变量的测量误差
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Implementation of the SIMEX algorithm for Accelerated Failure Time model with covariates subject to measurement error.
SIMEX算法加速失效时间模型的协变量的测量误差。
用法----------Usage----------
simexaft(formula = formula(data), data = parent.frame(),
SIMEXvariable, repeated = FALSE, repind = list(),
err.mat = err.mat, B = 50, lambda = seq(0, 2, 0.1),
extrapolation = "quadratic", dist = "weibull")
参数----------Arguments----------
参数：formula
specifies the model to be fitted, with the variables coming with data. This argument has the same format as the formula argument in the existing R function "survreg".
指定安装，与变量的数据模型。在现有的“的R函数”survreg“，这种说法有相同的格式，公式参数。
参数：data
optional data frame in which to interpret the varialbes occurring in the formula.
可选的数据框，其中解释发生在式varialbes。
参数：SIMEXvariable
the index of the covariate variables that are subject to measurement error.
受测量误差的协变量的索引。
参数：repeated
set to TRUE or FALSE to indicate if there are repeated measurements for the mis-measured variables.
设置为TRUE或FALSE表示，如果有反复测量，的误测得的变量。
参数：repind
the index of the repeated measurement variables for each mis-measured variable. It has an R list form. If repeated = TRUE, repind must be specify.
重复测量为每个误测得的变量的变量的索引。它的R列表形式。如果重复= TRUE，repind必须指定。
参数：err.mat
specifies the variables with measurement error, If repeated = FALSE, err.mat must be specify.
指定变量的测量误差，，如果重复= FALSE，err.mat必须指定。
参数：B
the number of simulated samples for the simulation step. The default is set to be 50.
模拟步骤的模拟样本的数目。默认设置为50。
参数：lambda
the vector of lambdas, the grids for the extrapolation step.
lambda表达式的矢量，网格的外推步骤。
参数：extrapolation
specifies the function form for the extrapolation step. The options are linear, quadratic and both. The default is set to be quadratic.(first 4 letters are enough)
的外推步骤指定的函数形式。线性，二次和两个选项。默认的设置为二次。（前4个字母是足够了）
参数：dist
specifies a parametric distribution that is assumed in AFT model. This argument is the same as the dist option in the existing R function "survreg". These include "weibull", "exponential", "gaussian", "logistic", "lognormal", and "loglogistic".
AFT模型是假设在指定参数分布。这种说法是在现有的“的R函数”survreg“dist选项相同。这些包括“威布尔”，“指数”，“高斯”，“MF”，“对数正态分布”，和“loglogistic。
Details
详细信息----------Details----------
If the SIMEXvariable is repeated measured then you only need to use arguments repeated and repind without mention err.mat. The summary.simex will contain repind.
如果SIMEXvariable重复测量，然后你只需要使用参数重复并没有提及err.mat repind。该summary.simex将包含repind的。
值----------Value----------
参数：coefficient
the corrected coefficients of the AFT model
的校正系数的AFT模型
参数：se
the standard deviation of each coefficient
每个系数的标准偏差
参数：pvalue
the p-value for the hypothesis of that coefficient equal zero
该系数为零的假设的p-值
参数：scalreg
the estimate of the scale
估计的规模
参数：theta
the estimates for every B and lambda
估计每个B和lambda
参数：lambda
the vector of lambdas for which the simulation step should be done
模拟步骤应做的矢量的lambda表达式
参数：B
the number of simulated samples for the simulation step.
模拟步骤的模拟样本的数目。
参数：formula
the model to be fitted in the survreg function
该模型将安装在survreg功能
参数：err.mat
the covariance matrix of the variables with measurement error
变量与测量误差的协方差矩阵的
参数：repind
the list contiains the names of the repeat measument variables
列表contiains重复流速 - 变量的名称
参数：extrapolation
the extrapolation method: linear ,quadratic are implemented (first 4 letters are enough)
外推法：线性，二次实施（第4个字母是足够的）
参数：SIMEXvariable
the vector contains the names of the variables with meansurement error
该向量含有的变量与meansurement错误的名称
（作者）----------Author(s)----------
Juan Xiong, Wenqing He and Grace Y. Yi
参考文献----------References----------
R-project.org/package=mvtnorm.
参见----------See Also----------
survreg, plotsimexaft
survreg，plotsimexaft
实例----------Examples----------
library("simexaft")
data("BHS")
dataset <- BHS
dataset$SBP <- log(dataset$SBP - 50)
###Naive AFT approach[＃＃朴素AFT方法]
formula <- Surv(SURVTIME,DTHCENS) ~ SBP + CHOL + AGE + BMI + SMOKE1 + SMOKE2
out1 <- survreg(formula = formula, data = dataset, dist = "weibull")
summary(out1)
###fit a AFT model with quadratic extrapolation[＃＃适合AFT与二次外推模型]
set.seed(120)
ind <- c("SBP", "CHOL")
err.mat <- diag(rep(0.5625, 2))
out2 <- simexaft(formula = formula, data = dataset, SIMEXvariable = ind,
repeated = FALSE, repind = list(), err.mat = err.mat, B = 50,
lambda = seq(0, 2, 0.1),extrapolation = "quadratic", dist = "weibull")
summary(out2)
#################### repeated measurements #################################[＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃重复测量，＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃ ＃＃＃＃]
data("rhDNase")
###true model[真实的模型＃＃]
rhDNase$fev.ave <- (rhDNase$fev + rhDNase$fev2)/2
output1 <- survreg(Surv(time2, status) ~ trt + fev.ave, data = rhDNase,
dist = "weibull")
summary(output1)
####sensitive analysis#####[＃＃＃＃＃＃＃＃敏感性分析]
set.seed(120)
fev.error <- rhDNase$fev + rnorm(length(rhDNase$fev), mean = 0,
sd = 0.15 * sd(rhDNase$fev))
fev.error2 <- rhDNase$fev2 + rnorm(length(rhDNase$fev2),mean = 0,
sd = 0.15 * sd(rhDNase$fev2))
dataset2 <- cbind(rhDNase[, c("time2", "status", "trt")], fev.error, fev.error2)
formula <- Surv(time2, status) ~ trt + fev.error
ind <- "fev.error"
########naive model using the average FEV value####################[模型中使用的平均容积值＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃幼稚]
fev.error.c <- (fev.error + fev.error2)/2
output2 <- survreg(Surv(time2, status) ~ trt + fev.error.c, data = rhDNase,
dist = "weibull")
summary(output2)
######use simexaft and apply the quadratic extrapolation######[＃＃＃＃＃使用simexaft＃＃＃＃＃＃和应用二次外推]
formula <- Surv(time2, status) ~ trt + fev.error
output3 <- simexaft(formula = formula, data = dataset2, SIMEXvariable = ind,
repeated=TRUE,repind=list(c("fev.error", "fev.error2")), err.mat=NULL,
B=50, lambda=seq(0,2, 0.1), extrapolation="quadratic", dist="weibull")
summary(output3)
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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 2012-9-30 02:39:39
