logistics regression

Fitting a logistic regression model using the predictors "balance"

The function "glm()" fits generalized linear models, a class of models that includes logistic regression as a special case

The function "glm()" is similar to that of "lm()", except that we have to pass on the argument "family=binomial" in order to fit a logistic regression model

Error in eval(family$initialize) : y values must be 0 <= y <= 1

family=binomaial not accepted.

binomial should be quoted so R will treat it as a character string and not as a name to be evaluated.

family = "binomial"

I tried that. Bit the same error message appeared.

Hmmm. Actually try binomial unquoted but with brackets as a function call.

family = binomial()

The following 3 examples all work , and give same result

(model_a <- glm(formula = vs ~ mpg, family = binomial, data = mtcars))
(model_b <- glm(formula = vs ~ mpg, family = "binomial", data = mtcars))
(model_c <- glm(formula = vs ~ mpg, family = binomial(), data = mtcars))

I think your post might have led me in the wrong direction by including two different errors and I focused on the first.
If you have an error about y value being the wrong type, it's probably because it's the wrong type for logistic regression, the Independent variable should have values between 0 and 1.

Please check and make sure the type of your response variable is binary. Binary Logistic Regression require logical data type (TRUE, FALSE) or binary (0, 1).