How to calculate standardized residuals in R
To calculate standardized residuals in R, you can follow these steps:
Fit a regression model using the
lm()
function. This function takes the formlm(formula, data)
, whereformula
specifies the relationship between the variables anddata
is the data frame containing the variables.Use the
residuals()
function to extract the residuals from the fitted model. This function takes the formresiduals(model)
, wheremodel
is the fitted model object obtained from thelm()
function.Calculate the mean and standard deviation of the residuals using the
mean()
andsd()
functions, respectively. These functions take the formmean(residuals)
andsd(residuals)
, whereresiduals
is the vector of residuals obtained from the previous step.Standardize the residuals by subtracting the mean and dividing by the standard deviation. This can be done using the formula
(residuals - mean(residuals)) / sd(residuals)
.
Here is an example that demonstrates these steps:
# Step 1: Fit a regression model
model <- lm(y ~ x, data = my_data)
# Step 2: Extract residuals
residuals <- residuals(model)
# Step 3: Calculate mean and standard deviation of residuals
residuals_mean <- mean(residuals)
residuals_sd <- sd(residuals)
# Step 4: Calculate standardized residuals
standardized_residuals <- (residuals - residuals_mean) / residuals_sd
The standardized_residuals
vector will contain the standardized residuals for each observation in the dataset.