Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----setup--------------------------------------------------------------------
library(rmdl)
## -----------------------------------------------------------------------------
# Look at potential data from the `mtcars` dataset
head(mtcars)
baseFormula <- mpg ~ wt + hp
rFormula <- fmls(mpg ~ wt + hp)
# Similar to the base formula
rFormula
## -----------------------------------------------------------------------------
# Uses a custom fit function to return linear models
listModels <-
rFormula |>
fit(.fn = lm, data = mtcars, raw = TRUE)
## -----------------------------------------------------------------------------
# Uses a custom fit function
rModel <-
rFormula |>
fit(.fn = lm, data = mtcars, raw = FALSE)
rModel
## -----------------------------------------------------------------------------
# An additional model to work with
r2Model <-
fmls(am ~ cyl + hp, pattern = "sequential") |>
fit(.fn = glm, family = "binomial", data = mtcars, raw = FALSE)
# Displays the two additional logistic regressions performed
r2Model
# Creation of a table of models
rTable <- model_table(mileage = rModel, automatic = r2Model)
rTable
## -----------------------------------------------------------------------------
fTable <-
rTable |>
flatten_models(exponentiate = TRUE, which = "automatic")
# Display contents
fTable
# Filter down to relevant models
fTable |>
dplyr::select(name, number, outcome, term, estimate, conf_low, conf_high, p_value, nobs)
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