# Many ways to do the same thing: linear regression

April 7, 2019
By

(This article was first published on R – Statistical Odds & Ends, and kindly contributed to R-bloggers)

One feature of R (could be positive, could be negative) is that there are many ways to do the same thing. In this post, I list out the different ways we can get certain results from a linear regression model. Feel free to comment if you know more ways other than those listed!

In what follows, we will use the linear regression object `lmfit`:

```data(mtcars)
lmfit <- lm(mpg ~ hp + cyl, data = mtcars)
```

Extracting coefficients of the linear model

```# print the lm object to screen
lmfit

# part of the summary output
summary(lmfit)

# extract from summary output
summary(lmfit)\$coefficients[, 1]

# use the coef function
coef(lmfit)

# extract using list syntax
lmfit\$coefficients
```

Getting fitted values for the training data set

```# use the predict function
predict(lmfit)

# extract from lm object
lmfit\$fitted.values
```

Getting residuals for the training data set

```# use the predict function
resid(lmfit)

# extract from lm object
lmfit\$residuals

# extract from lm summary
summary(lmfit)\$residuals
```

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