r - 每个自变量的线性回归循环分别针对因变量

Question

我想弄清楚如何创建循环或使用apply函数之一来针对因变量获取数据集中每个变量的单独1:1回归信息。

可以说我正在使用mtcars。我该如何用R代码编写数据帧中的每个变量，然后将其相对于MPG进行回归？

更好的是获得每个自变量的摘要并具有某种名称分配，例如x1 =，x2 = etc

summary(lm(mpg~eachvar,data=mtcars))

Answer 1

嗨，尝试这样的事情:

models <- lapply(paste("mpg", names(mtcars)[-1], sep = "~"), formula)
res.models <- lapply(models, FUN = function(x) {summary(lm(formula = x, data = mtcars))})
names(res.models) <- paste("mpg", names(mtcars)[-1], sep = "~")
res.models[["mpg~disp"]]


# Call:
# lm(formula = x, data = mtcars)

# Residuals:
#     Min      1Q  Median      3Q     Max 
# -4.8922 -2.2022 -0.9631  1.6272  7.2305 

# Coefficients:
#              Estimate Std. Error t value Pr(>|t|)    
# (Intercept) 29.599855   1.229720  24.070  < 2e-16 ***
# disp        -0.041215   0.004712  -8.747 9.38e-10 ***
# ---
# Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

# Residual standard error: 3.251 on 30 degrees of freedom
# Multiple R-squared:  0.7183,  Adjusted R-squared:  0.709 
# F-statistic: 76.51 on 1 and 30 DF,  p-value: 9.38e-10