How to extract coefficients from a model in R
· 1 min read · Updated March 15, 2026 · beginner
r statistics regression models
Extracting coefficients from fitted models is a common task in R.
Using coef
The primary function is coef:
model <- lm(mpg ~ cyl + disp, data = mtcars)
coef(model)
# (Intercept) cyl disp
# 34.660939 -1.587297 -0.020684
# Access by name
coef(model)["cyl"]
# cyl
# -1.587297Using broom
The broom package provides tidy data frames:
library(broom)
model <- lm(mpg ~ cyl + disp + hp, data = mtcars)
tidy(model)
# # A tibble: 4 × 5
# term estimate std.error statistic p.value
# <chr> <dbl> <dbl> <dbl> <dbl>
# 1 (Intercept) 34.0 2.65 12.8 4.4e-12
# 2 cyl -1.48 0.71 -2.09 4.8e-2
# ...GLM and Confidence Intervals
For logistic regression, coefficients are on the log-odds scale. Use exp() to convert to odds ratios:
model_glm <- glm(am ~ mpg + cyl, data = mtcars, family = binomial)
coef(model_glm)
exp(coef(model_glm))
# Confidence intervals
confint(model)
# 2.5 % 97.5 %
# (Intercept) 24.945 43.377
# cyl -2.363 -0.592