ff_permute | R Documentation |
Permuate explanatory variables to produce multiple output tables for common regression models
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, ... )
.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
|
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 |
include_full_model |
Logical. Include model using all |
base_on_top |
Logical. Base variables at top of table, or bottom of table. |
... |
Other arguments to |
Returns a list of data frame with the final model table.
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")
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