When the response variable is a proportion (example values include 0.23, 0.11, 0.78, 0.98), a quasibinomial model will run in R but a binomial model will not.

A binomial model can be estimated with proportions as outcome. See below:

prop.m1 <- glm(cbind(Successes, Total) ~ X1,
            data = df,
            family = binomial)

prop.m2 <- glm(Proportion ~ X1,
             data = df,
             family = binomial,
             weights = Total) # provide prior weights

When the response variable is a proportion (example values include 0.23, 0.11, 0.78, 0.98), a quasibinomial model will run in R but a binomial model will not.

A binomial model can be estimated with proportions as outcome. See below:

prop.m1 <- glm(cbind(Successes, Total - Successes) ~ X1,
            data = df,
            family = binomial)

prop.m2 <- glm(Proportion ~ X1,
             data = df,
             family = binomial,
             weights = Total) # provide prior weights