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Custom tidy method for binomial GLM results

Source: R/logistic_regression.R
tidy.glm.Rd

[Stable]

Helper method (for broom::tidy()) to prepare a data frame from a glm object with binomial family.

Usage

# S3 method for glm
tidy(x, conf_level = 0.95, at = NULL, ...)

Arguments

x

(glm)
logistic regression model fitted by stats::glm() with "binomial" family.

conf_level

(proportion)
confidence level of the interval.

at

(numeric or NULL)
optional values for the interaction variable. Otherwise the median is used.

...

additional arguments for the lower level functions.

Value

A data.frame containing the tidied model.

See also

h_logistic_regression for relevant helper functions.

Examples

library(dplyr)
library(broom)

adrs_f <- tern_ex_adrs %>%
  filter(PARAMCD == "BESRSPI") %>%
  filter(RACE %in% c("ASIAN", "WHITE", "BLACK OR AFRICAN AMERICAN")) %>%
  mutate(
    Response = case_when(AVALC %in% c("PR", "CR") ~ 1, TRUE ~ 0),
    RACE = factor(RACE),
    SEX = factor(SEX)
  )
formatters::var_labels(adrs_f) <- c(formatters::var_labels(tern_ex_adrs), Response = "Response")
mod1 <- fit_logistic(
  data = adrs_f,
  variables = list(
    response = "Response",
    arm = "ARMCD",
    covariates = c("AGE", "RACE")
  )
)
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
mod2 <- fit_logistic(
  data = adrs_f,
  variables = list(
    response = "Response",
    arm = "ARMCD",
    covariates = c("AGE", "RACE"),
    interaction = "AGE"
  )
)
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred

df <- tidy(mod1, conf_level = 0.99)
df2 <- tidy(mod2, conf_level = 0.99)