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#' @import dplyr %>% | |
#' @import purrr %||% | |
tbl_cmh <- function(data, case, exposure, strata, | |
label = NULL, | |
estimate_fun = gtsummary::style_ratio, | |
overall_or = TRUE, | |
overall_label = "Crude") { | |
# converting selectors to character names ------------------------------------ | |
case <- dplyr::select(data, {{ case }}) %>% names() | |
exposure <- dplyr::select(data, {{ exposure }}) %>% names() | |
strata <- dplyr::select(data, {{ strata }}) %>% names() | |
label <- | |
broom.helpers::.formula_list_to_named_list( | |
label, | |
data = select(data, dplyr::all_of(strata)) | |
) | |
# subsetting dataset and deleting missing obs -------------------------------- | |
data <- | |
data %>% | |
dplyr::select(dplyr::all_of(c(case, exposure, strata))) %>% | |
tidyr::drop_na() | |
# calcuating counts within stratum ------------------------------------------- | |
tbl <- | |
strata %>% | |
purrr::imap( | |
function(strata_variable, n) { | |
margin_assignment <- switch(n == 1 & overall_or == TRUE, "row") # only include crude for first row | |
df_strata <- | |
data %>% | |
dplyr::select(dplyr::all_of(c(case, strata_variable, exposure))) %>% | |
tidyr::nest(data = -dplyr::all_of(case)) %>% | |
dplyr::mutate( | |
tbl = purrr::map(data, ~gtsummary::tbl_cross(.x, label = label, | |
margin = margin_assignment, | |
margin_text = overall_label)) | |
) | |
gtsummary::tbl_merge(df_strata$tbl, tab_spanner = as.character(df_strata$case)) | |
} | |
) %>% | |
# stacking all tables across all stratum | |
gtsummary::tbl_stack() %>% | |
# moving the overall column to the top | |
gtsummary::modify_table_body( | |
dplyr::arrange, | |
dplyr::desc(.data$variable == "..total..") | |
) %>% | |
# remove automatic bolding | |
gtsummary::modify_table_header("label", bold = NA_character_) | |
# calculating ORs within stratum --------------------------------------------- | |
df_or <- | |
strata %>% | |
purrr::map_dfr( | |
~data %>% | |
dplyr::select(dplyr::all_of(c(.x, exposure, case))) %>% | |
tidyr::nest(data = -dplyr::all_of(.x)) %>% | |
dplyr::mutate( | |
variable = .x, | |
label = as.character(!!rlang::sym(.x)), | |
row_type = "level", | |
or = purrr::map_chr( | |
data, | |
~with(.x, effectsize::oddsratio(!!rlang::sym(exposure), !!rlang::sym(case))) %>% | |
as.data.frame() %>% | |
dplyr::mutate_at(dplyr::vars(.data$Odds_ratio, .data$CI_low, .data$CI_high), estimate_fun) %>% | |
dplyr::mutate(or = stringr::str_glue("{Odds_ratio} ({CI_low}, {CI_high})")) %>% | |
dplyr::pull(or) | |
) | |
) %>% | |
dplyr::select(.data$variable, .data$row_type, .data$label, .data$or) | |
) | |
if (overall_or == TRUE) { | |
df_crude_or <- | |
tibble::tibble(variable = "..total..") %>% | |
dplyr::mutate( | |
label = overall_label, | |
row_type = "label", | |
or = with(data, effectsize::oddsratio(!!rlang::sym(exposure), !!rlang::sym(case))) %>% | |
as.data.frame() %>% | |
dplyr::mutate_at(dplyr::vars(.data$Odds_ratio, .data$CI_low, .data$CI_high), estimate_fun) %>% | |
dplyr::mutate(or = stringr::str_glue("{Odds_ratio} ({CI_low}, {CI_high})")) %>% | |
dplyr::pull(or) | |
) | |
df_or <- dplyr::bind_rows(df_crude_or, df_or) | |
} | |
# adding ORs to gtsummary table | |
tbl <- | |
tbl %>% | |
gtsummary::modify_table_body( | |
dplyr::left_join, | |
df_or, | |
by = c("variable", "row_type", "label") | |
) %>% | |
gtsummary::modify_table_header("or", hide = FALSE, label = "**Odds Ratio**") | |
# adding CMH ORs to tbl ------------------------------------------------------ | |
df_cmh_or <- | |
strata %>% | |
purrr::map_dfr( | |
~stats::mantelhaen.test(data[[case]], data[[exposure]], data[[.x]]) %>% | |
broom::tidy() %>% | |
dplyr::mutate_at(dplyr::vars(estimate, conf.low, conf.high), ~estimate_fun(1 / .)) %>% | |
dplyr::mutate( | |
variable = .x, | |
row_type = "label", | |
cmh_or = glue::glue("{estimate} ({conf.high}, {conf.low})") | |
) %>% | |
dplyr::select(.data$variable, .data$row_type, .data$cmh_or, .data$p.value) | |
) | |
tbl <- | |
tbl %>% | |
gtsummary::modify_table_body( | |
dplyr::left_join, | |
df_cmh_or, | |
by = c("variable", "row_type") | |
) %>% | |
gtsummary::modify_table_header( | |
"cmh_or", | |
hide = FALSE, | |
label = "**CMH Odds Ratio**" | |
) %>% | |
gtsummary::modify_table_header( | |
"p.value", | |
hide = FALSE, | |
fmt_fun = gtsummary::style_pvalue, | |
label = "**p-value**" | |
) | |
# bolding all the column headers --------------------------------------------- | |
tbl$table_header <- | |
tbl$table_header %>% | |
dplyr::mutate( | |
label = dplyr::if_else( | |
hide == FALSE & !startsWith(label, "**") & !endsWith(label, "**"), | |
paste0("**", label, "**"), | |
label | |
), | |
spanning_header = dplyr::if_else( | |
hide == FALSE & !startsWith(spanning_header, "**") & !endsWith(spanning_header, "**"), | |
paste0("**", spanning_header, "**"), | |
spanning_header | |
) | |
) | |
# returning final table ------------------------------------------------------ | |
class(tbl) <- c("tbl_cmh", "gtsummary") | |
tbl | |
} | |
library(gtsummary) | |
library(dplyr) | |
trial %>% | |
# creating a dataset with case-control and exposure status | |
select(exposure = response, case = death, grade, stage) %>% | |
mutate(exposure = factor(exposure, labels = c("Not Exposed", "Exposed")), | |
case = factor(case, labels = c("Control", "Case"))) %>% | |
# calculating the CMH OR and tabling the results | |
tbl_cmh(case = case, | |
exposure = exposure, | |
strata = c(grade, stage), | |
label = grade ~ "Tumor Grade", | |
overall_or = TRUE, | |
overall_label = "Overall") %>% | |
# the table is a gtsummary object, so you can use add any general gtsummary function | |
bold_labels() %>% | |
bold_p() |
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With the new update of gtsummary, the tbl_cmh() function no longer works; there are things to fix.