Usage
s_num_patients(
x,
labelstr,
.N_col,
count_by = NULL,
unique_count_suffix = TRUE
)
s_num_patients_content(
df,
labelstr = "",
.N_col,
.var,
required = NULL,
count_by = NULL,
unique_count_suffix = TRUE
)
summarize_num_patients(
lyt,
var,
.stats = NULL,
.formats = NULL,
.labels = c(unique = "Number of patients with at least one event", nonunique =
"Number of events"),
indent_mod = lifecycle::deprecated(),
.indent_mods = 0L,
...
)
analyze_num_patients(
lyt,
vars,
.stats = NULL,
.formats = NULL,
.labels = c(unique = "Number of patients with at least one event", nonunique =
"Number of events"),
show_labels = c("default", "visible", "hidden"),
indent_mod = lifecycle::deprecated(),
.indent_mods = 0L,
...
)Arguments
- x
(
characterorfactor)
vector of patient IDs.- 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.- .N_col
(
count)
row-wise N (row group count) for the group of observations being analyzed (i.e. with no column-based subsetting) that is passed byrtables.- count_by
(
characterorfactor)
optional vector to be combined withxwhen countingnonuniquerecords.- unique_count_suffix
(
logical)
should"(n)"suffix be added tounique_countlabels. Defaults toTRUE.- df
(
data.frame)
data set containing all analysis variables.- .var, var
(
string)
single variable name that is passed byrtableswhen requested by a statistics function.- required
(
characterorNULL)
optional name of a variable that is required to be non-missing.- lyt
(
layout)
input layout where analyses will be added to.- .stats
(
character)
statistics to select for the table.- .formats
(named
characterorlist)
formats for the statistics.- .labels
(named
character)
labels for the statistics (without indent).- indent_mod
- .indent_mods
(named
integer)
indent modifiers for the labels. Defaults to 0, which corresponds to the unmodified default behavior. Can be negative.- ...
additional arguments for the lower level functions.
- vars
(
character)
variable names for the primary analysis variable to be iterated over.- show_labels
(
string)
label visibility: one of "default", "visible" and "hidden".
Value
-
s_num_patients()returns a namedlistof 3 statistics:unique: Vector of counts and percentages.nonunique: Vector of counts.unique_count: Counts.
s_num_patients_content()returns the same values ass_num_patients().
summarize_num_patients()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_num_patients_content()to the table layout.
analyze_num_patients()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_num_patients_content()to the table layout.
Details
In general, functions that starts with analyze* are expected to
work like rtables::analyze(), while functions that starts with summarize*
are based upon rtables::summarize_row_groups(). The latter provides a
value for each dividing split in the row and column space, but, being it
bound to the fundamental splits, it is repeated by design in every page
when pagination is involved.
Functions
s_num_patients(): Statistics function which counts the number of unique patients, the corresponding percentage taken with respect to the total number of patients, and the number of non-unique patients.s_num_patients_content(): Statistics function which counts the number of unique patients in a column (variable), the corresponding percentage taken with respect to the total number of patients, and the number of non-unique patients in the column.summarize_num_patients(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper forrtables::summarize_row_groups().analyze_num_patients(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper forrtables::analyze().
Examples
# Use the statistics function to count number of unique and nonunique patients.
s_num_patients(x = as.character(c(1, 1, 1, 2, 4, NA)), labelstr = "", .N_col = 6L)
#> $unique
#> [1] 3.0 0.5
#> attr(,"label")
#> [1] ""
#>
#> $nonunique
#> [1] 5
#> attr(,"label")
#> [1] ""
#>
#> $unique_count
#> [1] 3
#> attr(,"label")
#> [1] " (n)"
#>
s_num_patients(
x = as.character(c(1, 1, 1, 2, 4, NA)),
labelstr = "",
.N_col = 6L,
count_by = as.character(c(1, 1, 2, 1, 1, 1))
)
#> $unique
#> [1] 3.0 0.5
#> attr(,"label")
#> [1] ""
#>
#> $nonunique
#> [1] 4
#> attr(,"label")
#> [1] ""
#>
#> $unique_count
#> [1] 3
#> attr(,"label")
#> [1] " (n)"
#>
# Count number of unique and non-unique patients.
df <- data.frame(
USUBJID = as.character(c(1, 2, 1, 4, NA)),
EVENT = as.character(c(10, 15, 10, 17, 8))
)
s_num_patients_content(df, .N_col = 5, .var = "USUBJID")
#> $unique
#> [1] 3.0 0.6
#> attr(,"label")
#> [1] ""
#>
#> $nonunique
#> [1] 4
#> attr(,"label")
#> [1] ""
#>
#> $unique_count
#> [1] 3
#> attr(,"label")
#> [1] " (n)"
#>
df_by_event <- data.frame(
USUBJID = as.character(c(1, 2, 1, 4, NA)),
EVENT = as.character(c(10, 15, 10, 17, 8))
)
s_num_patients_content(df_by_event, .N_col = 5, .var = "USUBJID")
#> $unique
#> [1] 3.0 0.6
#> attr(,"label")
#> [1] ""
#>
#> $nonunique
#> [1] 4
#> attr(,"label")
#> [1] ""
#>
#> $unique_count
#> [1] 3
#> attr(,"label")
#> [1] " (n)"
#>
s_num_patients_content(df_by_event, .N_col = 5, .var = "USUBJID", count_by = "EVENT")
#> $unique
#> [1] 3.0 0.6
#> attr(,"label")
#> [1] ""
#>
#> $nonunique
#> [1] 3
#> attr(,"label")
#> [1] ""
#>
#> $unique_count
#> [1] 3
#> attr(,"label")
#> [1] " (n)"
#>
df_tmp <- data.frame(
USUBJID = as.character(c(1, 2, 1, 4, NA, 6, 6, 8, 9)),
ARM = c("A", "A", "A", "A", "A", "B", "B", "B", "B"),
AGE = c(10, 15, 10, 17, 8, 11, 11, 19, 17)
)
tbl <- basic_table() %>%
split_cols_by("ARM") %>%
add_colcounts() %>%
analyze_num_patients("USUBJID", .stats = c("unique")) %>%
build_table(df_tmp)
tbl
#> A B
#> (N=5) (N=4)
#> ——————————————————————————————————————————————————————————————————
#> Number of patients with at least one event 3 (60.0%) 3 (75.0%)