Title: | Create interface for rbmi and tern |
---|---|
Description: | `RBMI` tabulation with `rtables` and `tern` packages. |
Authors: | Joe Zhu [aut, cre], Jana Stoilova [aut], F. Hoffmann-La Roche AG [cph, fnd] |
Maintainer: | Joe Zhu <[email protected]> |
License: | MIT + file LICENSE |
Version: | 0.1.3 |
Built: | 2024-09-14 04:54:37 UTC |
Source: | https://github.com/insightsengineering/tern.rbmi |
rtables::make_afun()
on it. It is used as afun
in rtables::analyze()
.a_rbmi_lsmeans(df, .in_ref_col, show_relative = c("reduction", "increase"))
a_rbmi_lsmeans(df, .in_ref_col, show_relative = c("reduction", "increase"))
df |
input dataframe |
.in_ref_col |
boolean variable, if reference column is specified |
show_relative |
"reduction" if ( |
h_tidy_pool(x)
h_tidy_pool(x)
x |
( |
data("rbmi_test_data") pool_obj <- rbmi_test_data h_tidy_pool(pool_obj$pars[1:3])
data("rbmi_test_data") pool_obj <- rbmi_test_data h_tidy_pool(pool_obj$pars[1:3])
tern.rbmi
package. This is an pool object from the rbmi analysis, see
browseVignettes(package = "tern.rbmi")
rbmi_test_data
rbmi_test_data
An object of class pool
of length 5.
s_rbmi_lsmeans(df, .in_ref_col, show_relative = c("reduction", "increase"))
s_rbmi_lsmeans(df, .in_ref_col, show_relative = c("reduction", "increase"))
df |
input dataframe |
.in_ref_col |
boolean variable, if reference column is specified |
show_relative |
"reduction" if ( |
library(rtables) library(dplyr) library(broom) data("rbmi_test_data") pool_obj <- rbmi_test_data df <- tidy(pool_obj) s_rbmi_lsmeans(df[1, ], .in_ref_col = TRUE) s_rbmi_lsmeans(df[2, ], .in_ref_col = FALSE)
library(rtables) library(dplyr) library(broom) data("rbmi_test_data") pool_obj <- rbmi_test_data df <- tidy(pool_obj) s_rbmi_lsmeans(df[1, ], .in_ref_col = TRUE) s_rbmi_lsmeans(df[2, ], .in_ref_col = FALSE)
rbmi
pool
results.summarize_rbmi( lyt, ..., table_names = "rbmi_summary", .stats = NULL, .formats = NULL, .indent_mods = NULL, .labels = NULL )
summarize_rbmi( lyt, ..., table_names = "rbmi_summary", .stats = NULL, .formats = NULL, .indent_mods = NULL, .labels = NULL )
lyt |
( |
... |
additional argument. |
table_names |
( |
.stats |
( |
.formats |
(named |
.indent_mods |
(named |
.labels |
(named |
library(rtables) library(dplyr) library(broom) data("rbmi_test_data") pool_obj <- rbmi_test_data df <- tidy(pool_obj) basic_table() %>% split_cols_by("group", ref_group = levels(df$group)[1]) %>% split_rows_by("visit", split_label = "Visit", label_pos = "topleft") %>% summarize_rbmi() %>% build_table(df)
library(rtables) library(dplyr) library(broom) data("rbmi_test_data") pool_obj <- rbmi_test_data df <- tidy(pool_obj) basic_table() %>% split_cols_by("group", ref_group = levels(df$group)[1]) %>% split_rows_by("visit", split_label = "Visit", label_pos = "topleft") %>% summarize_rbmi() %>% build_table(df)
broom::tidy()
) to prepare a data frame from an
pool
rbmi
object containing the LS means and contrasts and multiple visits## S3 method for class 'pool' tidy(x, ...)
## S3 method for class 'pool' tidy(x, ...)
x |
( |
... |
Additional arguments. Not used. Needed to match generic signature only. |
A dataframe