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Functions for analyzing frequencies and fractions of occurrences by grade for patients with occurrence data. Multiple occurrences within one individual are counted once at the greatest intensity/highest grade level.
Usage
s_count_occurrences_by_grade(
df,
.var,
.N_col,
id = "USUBJID",
grade_groups = list(),
remove_single = TRUE,
labelstr = ""
)
a_count_occurrences_by_grade(
df,
.var,
.N_col,
id = "USUBJID",
grade_groups = list(),
remove_single = TRUE,
labelstr = ""
)
count_occurrences_by_grade(
lyt,
var,
var_labels = var,
show_labels = "default",
riskdiff = FALSE,
na_str = NA_character_,
nested = TRUE,
...,
table_names = var,
.stats = NULL,
.formats = NULL,
.indent_mods = NULL,
.labels = NULL
)
summarize_occurrences_by_grade(
lyt,
var,
na_str = NA_character_,
...,
.stats = NULL,
.formats = NULL,
.indent_mods = NULL,
.labels = NULL
)Arguments
- df
(
data.frame)
data set containing all analysis variables.- .var, var
(
string)
single variable name that is passed byrtableswhen requested by a statistics function.- .N_col
(
integer)
column-wise N (column count) for the full column being analyzed that is typically passed byrtables.- id
(
string)
subject variable name.- grade_groups
(named
listofcharacter)
containing groupings of grades.- remove_single
(
logical)TRUEto not include the elements of one-element grade groups in the the output list; in this case only the grade groups names will be included in the output.- labelstr
(
character)
label of the level of the parent split currently being summarized (must be present as second argument in Content Row Functions). Seertables::summarize_row_groups()for more information.- lyt
(
layout)
input layout where analyses will be added to.- var_labels
(
character)
labels to show in the result table.- show_labels
(
string)
label visibility: one of "default", "visible" and "hidden".- riskdiff
(
flag)
whether a risk difference column is present. When set toTRUE,add_riskdiff()must be used assplit_funin the prior column split of the table layout, specifying which columns should be compared. Seestat_propdiff_ci()for details on risk difference calculation.- na_str
(
string)
string used to replace allNAor empty values in the output.- nested
(
flag)
whether this layout instruction should be applied within the existing layout structure if possible (TRUE, the default) or as a new top-level element (FALSE). Ignored if it would nest a split. underneath analyses, which is not allowed.- ...
additional arguments for the lower level functions.
- table_names
(
character)
this can be customized in case that the samevarsare analyzed multiple times, to avoid warnings fromrtables.- .stats
(
character)
statistics to select for the table.- .formats
(named
characterorlist)
formats for the statistics. See Details inanalyze_varsfor more information on the"auto"setting.- .indent_mods
(named
integer)
indent modifiers for the labels. Defaults to 0, which corresponds to the unmodified default behavior. Can be negative.- .labels
(named
character)
labels for the statistics (without indent).
Value
s_count_occurrences_by_grade()returns a list of counts and fractions with one element per grade level or grade level grouping.
a_count_occurrences_by_grade()returns the corresponding list with formattedrtables::CellValue().
count_occurrences_by_grade()returns a layout object suitable for passing to further layouting functions, or tortables::build_table(). Adding this function to anrtablelayout will add formatted rows containing the statistics froms_count_occurrences_by_grade()to the table layout.
summarize_occurrences_by_grade()returns a layout object suitable for passing to further layouting functions, or tortables::build_table(). Adding this function to anrtablelayout will add formatted content rows containing the statistics froms_count_occurrences_by_grade()to the table layout.
Functions
s_count_occurrences_by_grade(): Statistics function which counts the number of patients by highest grade.a_count_occurrences_by_grade(): Formatted analysis function which is used asafunincount_occurrences_by_grade().count_occurrences_by_grade(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper forrtables::analyze().summarize_occurrences_by_grade(): Layout-creating function which can take content function arguments and additional format arguments. This function is a wrapper forrtables::summarize_row_groups().
See also
Relevant helper function h_append_grade_groups().
Examples
library(dplyr)
df <- data.frame(
USUBJID = as.character(c(1:6, 1)),
ARM = factor(c("A", "A", "A", "B", "B", "B", "A"), levels = c("A", "B")),
AETOXGR = factor(c(1, 2, 3, 4, 1, 2, 3), levels = c(1:5)),
AESEV = factor(
x = c("MILD", "MODERATE", "SEVERE", "MILD", "MILD", "MODERATE", "SEVERE"),
levels = c("MILD", "MODERATE", "SEVERE")
),
stringsAsFactors = FALSE
)
df_adsl <- df %>%
select(USUBJID, ARM) %>%
unique()
s_count_occurrences_by_grade(
df,
.N_col = 10L,
.var = "AETOXGR",
id = "USUBJID",
grade_groups = list("ANY" = levels(df$AETOXGR))
)
#> $count_fraction
#> $count_fraction$ANY
#> [1] 6.0 0.6
#>
#> $count_fraction$`1`
#> [1] 1.0 0.1
#>
#> $count_fraction$`2`
#> [1] 2.0 0.2
#>
#> $count_fraction$`3`
#> [1] 2.0 0.2
#>
#> $count_fraction$`4`
#> [1] 1.0 0.1
#>
#> $count_fraction$`5`
#> [1] 0 0
#>
#>
# We need to ungroup `count_fraction` first so that the `rtables` formatting
# function `format_count_fraction()` can be applied correctly.
afun <- make_afun(a_count_occurrences_by_grade, .ungroup_stats = "count_fraction")
afun(
df,
.N_col = 10L,
.var = "AETOXGR",
id = "USUBJID",
grade_groups = list("ANY" = levels(df$AETOXGR))
)
#> RowsVerticalSection (in_rows) object print method:
#> ----------------------------
#> row_name formatted_cell indent_mod row_label
#> 1 ANY 6 (60.0%) 0 ANY
#> 2 1 1 (10.0%) 0 1
#> 3 2 2 (20.0%) 0 2
#> 4 3 2 (20.0%) 0 3
#> 5 4 1 (10.0%) 0 4
#> 6 5 0 0 5
# Layout creating function with custom format.
basic_table() %>%
split_cols_by("ARM") %>%
add_colcounts() %>%
count_occurrences_by_grade(
var = "AESEV",
.formats = c("count_fraction" = "xx.xx (xx.xx%)")
) %>%
build_table(df, alt_counts_df = df_adsl)
#> A B
#> (N=3) (N=3)
#> ————————————————————————————————————————
#> MILD 0.00 (0.00%) 2.00 (66.67%)
#> MODERATE 1.00 (33.33%) 1.00 (33.33%)
#> SEVERE 2.00 (66.67%) 0.00 (0.00%)
# Define additional grade groupings.
grade_groups <- list(
"-Any-" = c("1", "2", "3", "4", "5"),
"Grade 1-2" = c("1", "2"),
"Grade 3-5" = c("3", "4", "5")
)
basic_table() %>%
split_cols_by("ARM") %>%
add_colcounts() %>%
count_occurrences_by_grade(
var = "AETOXGR",
grade_groups = grade_groups
) %>%
build_table(df, alt_counts_df = df_adsl)
#> A B
#> (N=3) (N=3)
#> —————————————————————————————————
#> -Any- 3 (100%) 3 (100%)
#> Grade 1-2 1 (33.3%) 2 (66.7%)
#> 1 0 1 (33.3%)
#> 2 1 (33.3%) 1 (33.3%)
#> Grade 3-5 2 (66.7%) 1 (33.3%)
#> 3 2 (66.7%) 0
#> 4 0 1 (33.3%)
#> 5 0 0
# Layout creating function with custom format.
basic_table() %>%
add_colcounts() %>%
split_rows_by("ARM", child_labels = "visible", nested = TRUE) %>%
summarize_occurrences_by_grade(
var = "AESEV",
.formats = c("count_fraction" = "xx.xx (xx.xx%)")
) %>%
build_table(df, alt_counts_df = df_adsl)
#> all obs
#> (N=6)
#> ——————————————————————————
#> A
#> MILD 0.00 (0.00%)
#> MODERATE 1.00 (16.67%)
#> SEVERE 2.00 (33.33%)
#> B
#> MILD 2.00 (33.33%)
#> MODERATE 1.00 (16.67%)
#> SEVERE 0.00 (0.00%)
basic_table() %>%
add_colcounts() %>%
split_rows_by("ARM", child_labels = "visible", nested = TRUE) %>%
summarize_occurrences_by_grade(
var = "AETOXGR",
grade_groups = grade_groups
) %>%
build_table(df, alt_counts_df = df_adsl)
#> all obs
#> (N=6)
#> ———————————————————————
#> A
#> -Any- 3 (50.0%)
#> Grade 1-2 1 (16.7%)
#> 1 0
#> 2 1 (16.7%)
#> Grade 3-5 2 (33.3%)
#> 3 2 (33.3%)
#> 4 0
#> 5 0
#> B
#> -Any- 3 (50.0%)
#> Grade 1-2 2 (33.3%)
#> 1 1 (16.7%)
#> 2 1 (16.7%)
#> Grade 3-5 1 (16.7%)
#> 3 0
#> 4 1 (16.7%)
#> 5 0