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I am working with several large databases (e.g. PISA and NAEP) that use a complex survey design with replicate weights and multiple plausible values. I can address the former using the survey package. However, does there exist an R package/function to analyze the latter?

For reference, I have found this article to provide a good overview of the issue: http://www.ierinstitute.org/fileadmin/Documents/IERI_Monograph/IERI_Monograph_Volume_02_Chapter_01.pdf

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我不确定“合理值”的一般概念与使用多重插补来生成几组插补值（例如 Amelia 包所做的）有何不同。但是 Thomas Lumley 的 mitools 包可用于组合各种估算值集，并且它可能用于组合您的合理值集以获得估计的“正确”标准误差。

于 2012-06-04T20:50:32.183 回答
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Daniel Caro 为大规模评估开发了一个 R 包。你可以在这里找到它http://cran.r-project.org/web/packages/intsvy/index.html

这是使用回归命令的代码示例，而不是数学上的合理值：

## Not run:
# Table I.2.3a, p. 305, International Report 2012
pisa.reg.pv(pvlabel="MATH", x="ST04Q01", by = "IDCNTRYL", data=pisa)

虽然，我不确定这个包是否可以用来分析 NAEP 数据。我希望这能满足您的目的；至少部分。

于 2015-05-23T00:55:06.333 回答
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As of survey version 3.36 there's withPV

data(pisamaths, package="mitools")
des<-svydesign(id=~SCHOOLID+STIDSTD, strata=~STRATUM, nest=TRUE,
    weights=~W_FSCHWT+condwt, data=pisamaths)

options(survey.lonely.psu="remove")

results<-withPV(list(maths~PV1MATH+PV2MATH+PV3MATH+PV4MATH+PV5MATH),
   data=des,
   action=quote(svyglm(maths~ST04Q01*(PCGIRLS+SMRATIO)+MATHEFF+OPENPS, design=des)))

summary(MIcombine(results))
于 2019-05-07T00:02:03.223 回答