Extract Regression P Value in R

Question

I am performing multiple regressions on different columns in a query file. I've been tasked with extracting certain results from the regression function lm in R.

So far I have,

> reg <- lm(query$y1 ~ query$x1 + query$x2)
> summary(reg)

Call:
lm(formula = query$y1 ~ query$x1 + query$x2)

Residuals:
    1     2     3     4 
  7.68 -4.48 -7.04  3.84 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  1287.26     685.75   1.877    0.312
query$x1      -29.30      20.92  -1.400    0.395
query$x2     -116.90      45.79  -2.553    0.238

Residual standard error: 11.97 on 1 degrees of freedom
Multiple R-squared:  0.9233,    Adjusted R-squared:  0.7699 
F-statistic: 6.019 on 2 and 1 DF,  p-value: 0.277

To extract the coefficients, r-squared and F statistics I use the following:

reg$coefficients
summary(reg)$r.squared
summary(reg)$fstatistic

I would like to also extract the p-value of 0.277.

Is there a piece of code that could do this?

Thanks

Answer 1

I would recommend using the "broom" package as a good practice to go forward with those cases (where you might need to create a data frame from a model fit output).

Check this as a simple example:

library(broom)

dt = data.frame(mtcars) # example dataset

model = lm(mpg ~ disp + wt, data = dt) # fit a model

summary(model) # usual summary of a model fit

tidy(model) # get coefficient table as a data frame

glance(model) # get rest of stats as a data frame

glance(model)$p.value # get p value