Created
May 11, 2021 12:14
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function to display multinomial regression models in wide format
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set.seed(20210511) | |
library(gtsummary) | |
library(magrittr) | |
multinom_pivot_wider <- function(x) { | |
# check inputs match expectatations | |
if (!inherits(x, "tbl_regression") || !inherits(x$model_obj, "multinom")) { | |
stop("`x=` must be class 'tbl_regression' summary of a `nnet::multinom()` model.") | |
} | |
# create tibble of results | |
df <- tibble::tibble(outcome_level = unique(x$table_body$groupname_col)) | |
df$tbl <- | |
purrr::map( | |
df$outcome_level, | |
function(lvl) { | |
gtsummary::modify_table_body( | |
x, | |
~dplyr::filter(.x, .data$groupname_col %in% lvl) %>% | |
dplyr::ungroup() %>% | |
dplyr::select(-.data$groupname_col) | |
) | |
} | |
) | |
tbl_merge(df$tbl, tab_spanner = paste0("**", df$outcome_level, "**")) | |
} | |
# dummy data | |
crime <- | |
data.frame( | |
city = sample(c("SF", "AR", "NYC", "MN"), 13000, replace = TRUE), | |
year = sample(as.factor(c(1990, 2000, 1999, 1989)), 13000, replace = TRUE) | |
) | |
# multinom model tabulated with gtsummary | |
tbl <- | |
nnet::multinom(city ~ year, data = crime) %>% | |
tbl_regression(exponentiate = TRUE) %>% | |
multinom_pivot_wider() | |
Thank you very much, it's super useful!
The custom function works great, thanks.
I am now trying it with multiple models but I need to distinguish the model header from the the table_spanner argument. See the modified code below.
Is it possible to have 1) one spanner to distinguish the models and 2) one spanner to identify the categories in the factor dependent variable?
Thanks!
set.seed(20210511)
library(gtsummary)
library(magrittr)
multinom_pivot_wider <- function(x) {
# check inputs match expectatations
if (!inherits(x, "tbl_regression") || !inherits(x$model_obj, "multinom")) {
stop("`x=` must be class 'tbl_regression' summary of a `nnet::multinom()` model.")
}
# create tibble of results
df <- tibble::tibble(outcome_level = unique(x$table_body$groupname_col))
df$tbl <-
purrr::map(
df$outcome_level,
function(lvl) {
gtsummary::modify_table_body(
x,
~dplyr::filter(.x, .data$groupname_col %in% lvl) %>%
dplyr::ungroup() %>%
dplyr::select(-.data$groupname_col)
)
}
)
tbl_merge(df$tbl, tab_spanner = paste0("**", df$outcome_level, "**"))
}
# dummy data
crime <-
data.frame(
city = sample(c("SF", "AR", "NYC", "MN"), 13000, replace = TRUE),
year = sample(as.factor(c(1990, 2000, 1999, 1989)), 13000, replace = TRUE)
)
# now creating two models
tbl1 <-
nnet::multinom(city ~ year, data = crime) %>%
tbl_regression(exponentiate = TRUE) %>%
multinom_pivot_wider()
tbl2 <-
nnet::multinom(city ~ year, data = crime) %>%
tbl_regression(exponentiate = TRUE) %>%
multinom_pivot_wider()
# merging
tbl_merge(tbls = list(tbl1, tbl2), tab_spanner = c("**Tbl1**", "**Tbl2**"))
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Thank you a million times!