在R中的数据框中的列子集上拟合模型 [英] Fit model on a subset of columns in dataframe in R

问题描述

我正在尝试在协变量的子集上使用lm()和matchit().我已经生成了任意数量的带有前缀"covar"的列，即"covar.1"，"covar.2"等.我想做类似的事情

I'm trying to use lm() and matchit() on a subset of covariates. I have generated an arbitrary number of columns with prefix "covar", i.e. "covar.1", "covar.2", etc. I'd like to do something like

lm(group〜covars，data = df)

lm(group ~ covars, data=df)

其中covars是字符串c("covar.1"，"covar.2"，...)的向量.

where covars is a vector of strings c("covar.1", "covar.2", ...).

我尝试过类似的事情

  cols <- colnames(df)
  covars <- cols[grep("covar", colnames(df))]
  m.out <- matchit(group ~ covars, data=df, method="nearest", distance="logit", caliper=.20)

但得到了variable lengths differ (found for 'covars').

仅使用covars和group定义新的数据框是可行的，但是使用matchit违反了我的目的，因为我也希望匹配的数据具有其他列，而不仅仅是我选择作为匹配对象的covars.

Defining a new dataframe only with covars and group can work but that defeats my purpose using matchit because I want the matched data to have other columns, too, not just covars I picked to be the matched on.

这似乎是一件容易的事，但经过一番谷歌搜索后，我不知何故.不知道那里的R公式期望作为列的子集.感谢您的帮助.

This seems to be an easy task but somehow I can't figure out after some googling. Not sure what R formula expects there as subset of columns. Any help is appreciated.

推荐答案

您可能想使用as.formula.
尝试这样做:

You might want to use as.formula.
Try doing this:

替换group ~ covars

与as.formula(paste('group','~', paste(covars, collapse="+"))))

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