tidy.geeglm {broom} | R Documentation |
Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
## S3 method for class 'geeglm' tidy(x, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, ...)
x |
A |
conf.int |
Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to |
conf.level |
The confidence level to use for the confidence interval
if |
exponentiate |
Logical indicating whether or not to exponentiate the
the coefficient estimates. This is typical for logistic and multinomial
regressions, but a bad idea if there is no log or logit link. Defaults
to |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
If conf.int = TRUE
, the confidence interval is computed with
the an internal confint.geeglm()
function.
If you have missing values in your model data, you may need to
refit the model with na.action = na.exclude
or deal with the
missingness in the data beforehand.
A tibble::tibble()
with columns:
regresion |
TRUE |
library(geepack) data(state) ds <- data.frame(state.region, state.x77) geefit <- geeglm(Income ~ Frost + Murder, id = state.region, data = ds, family = gaussian, corstr = "exchangeable" ) tidy(geefit) tidy(geefit, conf.int = TRUE)