ff_permute: Permuate explanatory variables to produce multiple output...

In finalfit: Quickly Create Elegant Regression Results Tables and Plots when Modelling

Permuate explanatory variables to produce multiple output tables for common regression models

Description

Permuate explanatory variables to produce multiple output tables for common regression models

Usage

ff_permute(
  .data,
  dependent = NULL,
  explanatory_base = NULL,
  explanatory_permute = NULL,
  multiple_tables = FALSE,
  include_base_model = TRUE,
  include_full_model = TRUE,
  base_on_top = TRUE,
  ...
)

finalfit_permute(
  .data,
  dependent = NULL,
  explanatory_base = NULL,
  explanatory_permute = NULL,
  multiple_tables = FALSE,
  include_base_model = TRUE,
  include_full_model = TRUE,
  base_on_top = TRUE,
  ...
)

Arguments

.data	Data frame or tibble.
dependent	Character vector of length 1: quoted name of dependent variable. Can be continuous, a binary factor, or a survival object of form Surv(time, status).
explanatory_base	Character vector of any length: quoted name(s) of base model explanatory variables.
explanatory_permute	Character vector of any length: quoted name(s) of explanatory variables to permute through models.
multiple_tables	Logical. Multiple model tables as a list, or a single table including multiple models.
include_base_model	Logical. Include model using explanatory_base variables only.
include_full_model	Logical. Include model using all explanatory_base and explanatory_permute variables.
base_on_top	Logical. Base variables at top of table, or bottom of table.
...	Other arguments to finalfit

Value

Returns a list of data frame with the final model table.

Examples

explanatory_base = c("age.factor", "sex.factor")
explanatory_permute = c("obstruct.factor", "perfor.factor", "node4.factor")

# Linear regression
colon_s %>%
  finalfit_permute("nodes", explanatory_base, explanatory_permute)

# Cox proportional hazards regression
colon_s %>%
  finalfit_permute("Surv(time, status)", explanatory_base, explanatory_permute)

# Logistic regression
# colon_s %>%
#   finalfit_permute("mort_5yr", explanatory_base, explanatory_permute)

# Logistic regression with random effect (glmer)
# colon_s %>%
#   finalfit_permute("mort_5yr", explanatory_base, explanatory_permute,
#     random_effect = "hospital")

finalfit documentation built on Nov. 17, 2023, 1:09 a.m.