在许多模型中使用其他自变量的所有可能组合获取特定变量的p值 [英] Get p values for a specific variable in many models with all possible combinations of other independent variables

问题描述

我正在尝试使用一组自变量的所有可能组合来运行许多回归模型.

I am trying to run many regression models with all possible combinations of a set of independent variables.

在此示例中，我对cyl的系数以及xlist中列出的其他变量的所有可能组合感兴趣.

In this example, I am interested in the coefficients of cyl with all possible combinations of other variables listed in xlist.

df <- mtcars
md <- "mpg ~ cyl" 
xlist <- c("disp", "hp", "am")
n <- length(xlist)
# get a list of all possible combinations of xlist 
comb_lst <- unlist(lapply(1:n, function(x) combn(xlist, x, simplify=F)), recursive = F)
# get a list of all models
md_lst <- lapply(comb_lst, function(x) paste(md, "+", paste(x, collapse = "+")))
# run those models and obtain coefficients for cyl
coefs <- unlist(lapply(md_lst, function(x) lm(as.formula(x),data=df)$coe[2]))

获得cyl的所有系数都很好.但是，我不知道如何获取与每个系数相对应的p值.

It works fine to get all coefficients for cyl. However, I don't know how to get the p value corresponding to each of those coefficients.

pvalues <- lapply(md, function(x) lm(as.formula(x),data=df)$?[2]))

任何建议将不胜感激.

Any suggestions would be appreciated.

推荐答案

免责声明:: 此答案使用

Disclaimer:: This answer uses the developer version of manymodelr that I also happen to have written. You can then go on to choose only those variables you are interested in.

Map(function(x) manymodelr::extract_model_info(x,"p_value"),
  lapply(md_lst, function(x) do.call(lm, list(formula = x, data=mtcars))))

# Just cyl
Map(function(x) manymodelr::extract_model_info(x,"p_value")["cyl"],
  lapply(md_lst, function(x) do.call(lm, list(formula = x, data=mtcars))))

如果您不想使用软件包:

Map(function(x) coef(summary(x))[,4]["cyl"],
  lapply(md_lst, function(x) do.call(lm, list(formula = x, data=mtcars))))

结果::(第一部分)

[[1]]
 (Intercept)          cyl         disp 
4.022869e-14 3.366495e-02 5.418572e-02 

[[2]]
 (Intercept)          cyl           hp 
1.620660e-16 4.803752e-04 2.125285e-01 

[[3]]
 (Intercept)          cyl           am 
7.694408e-14 1.284560e-07 5.635445e-02 

[[4]]
 (Intercept)          cyl         disp           hp 
1.537198e-13 1.349044e-01 8.092901e-02 3.249519e-01 

[[5]]
 (Intercept)          cyl         disp           am 
2.026114e-12 2.823412e-02 1.544849e-01 1.610559e-01 

[[6]]
 (Intercept)          cyl           hp           am 
9.270924e-12 8.635578e-02 1.692706e-02 5.464020e-03 

[[7]]
 (Intercept)          cyl         disp           hp           am 
3.724625e-11 2.800850e-01 4.760672e-01 4.416647e-02 2.520516e-02 

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