CODEWITHSUNDEEP
rstatistics-bootstrap
enfield
enfield

Reputation: 121

Predictor variable not found for bootstrapping

I have to bootstrap a logistic regression model on the 'birthwt' dataset from MASS. However, when I run my code for the bootstrap, I get the following error

Error in eval(predvars, data, env) : object 'low' not found

I don't understand why I get this error, since 'low' is among the variable names in the model.

Why do I get this error? Any feedback is appreciated!

data(birthwt, package = "MASS")

data <- as.data.frame(birthwt)
# converting predictor variable into factor
data$low <- as.factor(data$low)

pmod <- glm(low ~ . - bwt - age - ftv, data = data, family = binomial)
boot_results <- car::Boot(pmod, R = 100)

Upvotes: 1

Views: 29

Answers (1)

jpsmith
jpsmith

Reputation: 17656

I've only ever used the boot::boot function for bootstrapping, but looking at the help page for car::Boot, it states:

"This function provides a simple front-end to the boot function in the boot package that is tailored to bootstrapping based on regression models..."

So the long way around using boot::boot would be to first define your logistic regression for bootstrapping and then bootstrap on that function:

boot_logreg <- function(my_data, indices) {
  coef(glm(low ~ . - bwt - age - ftv, data = my_data[indices, ], family = binomial))
}

set.seed(123)  # Seed for reproducibility, not required
boot_results <- boot::boot(data, boot_logreg, R = 1000)

# ORDINARY NONPARAMETRIC BOOTSTRAP
# 
# Call:
# boot::boot(data = data, statistic = boot_logreg, R = 1000)

# Bootstrap Statistics :
#        original       bias    std. error
# t1* -0.80364418  0.070440226 1.238398503
# t2* -0.01294747 -0.001190249 0.008038214
# t3*  0.46913122  0.012766086 0.228166001
# t4*  0.94817154  0.021266241 0.426519541
# t5*  0.49145146  0.050717609 0.450790533
# t6*  1.83315979  0.198129583 1.311930532
# t7*  0.74793544  0.027657403 0.559801377

Upvotes: 0

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