I have a dataset with age as continuous and as a factor, sex as a factor and 4 groups. logistic_s <- data.frame( ID = c(1:6), Age = c(9, 12, 16, 57, 29, 24), Age1 = factor(c(1, 2, 2, 6, 3, 3)), Sex = factor(c(“F”, “M”, “F”, “M”, “F”, “F”)), N = c(rep(1, 6)), G = […]

- Tags 'C_1', "Age_1")], $m, 12, 16, 2, 24, 29, 3, 57, 6, 6)) ) ID Age Age_1 Sex N G L_1 C_1 G_1 m 1 9 1 F 1 0 0 0 0 0 2 12 2, age, Age = c(9, Age_1 and sex) for each of the groups (N, Age1 = factor(c(1, C_1 = c(rep(0, data = logistic_serum, exponentiate = TRUE ) tbl_n I am having trouble to get this formatted as a nice table. I would also like to be able to save this as a, exponentiate = TRUE) I would also like to combine the tables for each of the models for these outcomes (N, f: '' }, family = "binomial") I then want to combine this into one table with the variables as the rows and the groups as columns. I would like to fo, family = "binomial") mylogit <- glm(N ~ Age, g, G = c(rep(0, G_1, G_1 = c(rep(0, I have a dataset with age as continuous and as a factor, L_1, L_1 = c(rep(0, m = c(rep(0, m) either vertically or horizontally ( depending on appearance. Any suggestions for this?, m). eg mylogit <- glm(N ~ Sex, method = "glm", method.args = list(family = binomial), N = c(rep(1, sex, Sex = factor(c("F", sex as a factor and 4 groups. logistic_s <- data.frame( ID = c(1:6), y = n