Patient Counts with Abnormal Range Values

Usage

s_count_abnormal(
  df,
  .var,
  abnormal = list(Low = "LOW", High = "HIGH"),
  variables = list(id = "USUBJID", baseline = "BNRIND"),
  exclude_base_abn = FALSE
)

a_count_abnormal(
  df,
  .var,
  abnormal = list(Low = "LOW", High = "HIGH"),
  variables = list(id = "USUBJID", baseline = "BNRIND"),
  exclude_base_abn = FALSE
)

count_abnormal(
  lyt,
  var,
  ...,
  table_names = var,
  .stats = NULL,
  .formats = NULL,
  .labels = NULL,
  .indent_mods = NULL
)

Arguments

df

(data.frame)
data set containing all analysis variables.

.var, var

(string)
single variable name that is passed by rtables when requested by a statistics function.

abnormal

(named list)
list identifying the abnormal range level(s) in var. Defaults to list(Low = "LOW", High = "HIGH") but you can also group different levels into the named list, for example, abnormal = list(Low = c("LOW", "LOW LOW"), High = c("HIGH", "HIGH HIGH")).

variables

(named list of string)
list of additional analysis variables.

exclude_base_abn

(flag)
whether to exclude subjects with baseline abnormality from numerator and denominator.

lyt

(layout)
input layout where analyses will be added to.

...

additional arguments for the lower level functions.

table_names

(character)
this can be customized in case that the same vars are analyzed multiple times, to avoid warnings from rtables.

.stats

(character)
statistics to select for the table.

.formats

(named character or list)
formats for the statistics.

.labels

(named character)
labels for the statistics (without indent).

.indent_mods

(named integer)
indent modifiers for the labels. Defaults to 0, which corresponds to the unmodified default behavior. Can be negative.

Value

• s_count_abnormal() returns the statistic fraction which is a vector with num and denom counts of patients.

• a_count_abnormal() returns the corresponding list with formatted rtables::CellValue().

• count_abnormal() returns a layout object suitable for passing to further layouting functions, or to rtables::build_table(). Adding this function to an rtable layout will add formatted rows containing the statistics from s_count_abnormal() to the table layout.

Functions

• s_count_abnormal(): Statistics function which counts patients with abnormal range values for a single abnormal level.

• a_count_abnormal(): Formatted analysis function which is used as afun in count_abnormal().

• count_abnormal(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper for rtables::analyze().

Note

• count_abnormal() only works with a single variable containing multiple abnormal levels.

• df should be filtered to include only post-baseline records.

• the denominator includes patients that might have other abnormal levels at baseline, and patients with missing baseline. Patients with these abnormalities at baseline can be optionally excluded from numerator and denominator.

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

df <- data.frame(
  USUBJID = as.character(c(1, 1, 2, 2)),
  ANRIND = factor(c("NORMAL", "LOW", "HIGH", "HIGH")),
  BNRIND = factor(c("NORMAL", "NORMAL", "HIGH", "HIGH")),
  ONTRTFL = c("", "Y", "", "Y"),
  stringsAsFactors = FALSE
)

# Select only post-baseline records.
df <- df %>%
  filter(ONTRTFL == "Y")
# Layout creating function.
basic_table() %>%
  count_abnormal(var = "ANRIND", abnormal = list(high = "HIGH", low = "LOW")) %>%
  build_table(df)
#>         all obs 
#> ————————————————
#> high   1/2 (50%)
#> low    1/2 (50%)

# Passing of statistics function and formatting arguments.
df2 <- data.frame(
  ID = as.character(c(1, 1, 2, 2)),
  RANGE = factor(c("NORMAL", "LOW", "HIGH", "HIGH")),
  BL_RANGE = factor(c("NORMAL", "NORMAL", "HIGH", "HIGH")),
  ONTRTFL = c("", "Y", "", "Y"),
  stringsAsFactors = FALSE
)

# Select only post-baseline records.
df2 <- df2 %>%
  filter(ONTRTFL == "Y")

basic_table() %>%
  count_abnormal(
    var = "RANGE",
    abnormal = list(low = "LOW", high = "HIGH"),
    variables = list(id = "ID", baseline = "BL_RANGE")
  ) %>%
  build_table(df2)
#>         all obs 
#> ————————————————
#> low    1/2 (50%)
#> high   1/2 (50%)