saws-package(saws)
saws-package()所属R语言包:saws
Small-Sample Adjustments for Wald tests Using Sandwich Estimators
沃尔德测试,采用三明治估计的小样本调整
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Tests coefficients with sandwich estimator of variance and with small samples. Regression types supported are gee, cox regression, and conditional logistic regression.
夹心方差估计的小样本试验系数。回归支持的类型有哎呀,Cox回归,和条件logistic回归分析。
Details
详细信息----------Details----------
The main function of this package is saws, which takes output from some regression models (gee, cox regression, conditional logistic regression) and gives inferences (confidence intervals, p-values) using small sample adjusted sandwich estimators of variance.
这个包的主要功能是saws,需要输出一些回归模型(哎呀,Cox回归,条件Logistic回归),并给出了使用小样本调整三明治估计方差的推断(置信区间,p值)。
In this version of the package, there are two specialized functions for creating regression output for use in the saws function: mgee and clogistCalc. The function mgee is a slight modification of the gee function that creates the 'u' matrix and the 'omega' array. The 'coefficients' is a vector with p parameter estimates, and is a standard output from the regression. The matrix 'u' is K by p with u[i,] the ith estimating equation, where there are K approximately independent estimating equations. The array 'omega' is K by p by p where omega[i,,] is a p by p matrix estimating - du/dbeta (here beta=coefficients). See Fay and Graubard (2001) for details.
在这个版本的软件包中,有两个特殊的功能,用于创建回归输出,用于saws功能:mgee和clogistCalc。函数mgee是一个轻微的修改gee函数创建的“U”矩阵“欧米茄”阵列。的“系数”是一个向量与p参数估计,和是一个标准的输出从回归。矩阵U是K p的U [我]的第i个估计方程,其中有K约独立的估计方程。 “欧米茄”阵列由p是K欧米茄[我]是AP p矩阵估计由P - 杜/ dbeta(β=系数)。有关详细信息,请参阅费伊和Graubard的(2001年)。
The cox regression function is not included in this version. It should be included in a future version. There is a demo recreating the example in Fay and Graubard (2001).
Cox回归函数不包含在这个版本。它应该包含在将来的版本中。重新Fay和Graubard(2001)的例子中有一个演示。
(作者)----------Author(s)----------
M.P. Fay
Maintainer: Michael Fay <mfay@niaid.nih.gov>
参考文献----------References----------
实例----------Examples----------
library(gee)
data(warpbreaks)
mout<-mgee(breaks~tension,id=wool, data=warpbreaks, corstr="exchangeable")
saws(mout)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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