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Patient Counts with Abnormal Range Values by Baseline Status

Source: R/abnormal_by_baseline.R
abnormal_by_baseline.Rd

[Stable]

Primary analysis variable .var indicates the abnormal range result (character or factor), and additional analysis variables are id (character or factor) and baseline (character or factor). For each direction specified in abnormal (e.g. high or low) we condition on baseline range result and count patients in the numerator and denominator as follows:

  • Not <Abnormal>

    • denom: the number of patients without abnormality at baseline (excluding those with missing baseline)

    • num: the number of patients in denom who also have at least one abnormality post-baseline

  • <Abnormal>

    • denom: the number of patients with abnormality at baseline

    • num: the number of patients in denom who also have at least one abnormality post-baseline

  • Total

    • denom: the number of patients with at least one valid measurement post-baseline

    • num: the number of patients in denom who also have at least one abnormality post-baseline

Usage 

s_count_abnormal_by_baseline(
  df,
  .var,
  abnormal,
  na_level = "<Missing>",
  variables = list(id = "USUBJID", baseline = "BNRIND")
)

a_count_abnormal_by_baseline(
  df,
  .var,
  abnormal,
  na_level = "<Missing>",
  variables = list(id = "USUBJID", baseline = "BNRIND")
)

count_abnormal_by_baseline(
  lyt,
  var,
  abnormal,
  ...,
  table_names = abnormal,
  .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

(character)
identifying the abnormal range level(s) in .var.

na_level

(string)
the explicit na_level argument you used in the pre-processing steps (maybe with df_explicit_na()). The default is "<Missing>".

variables

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

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.

Value

  • s_count_abnormal_by_baseline() returns statistic fraction which is a named list with 3 labeled elements: not_abnormal, abnormal, and total. Each element contains a vector with num and denom patient counts.

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

  • count_abnormal_by_baseline() 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_by_baseline() to the table layout.

Functions

  • s_count_abnormal_by_baseline(): Statistics function for a single abnormal level.

  • a_count_abnormal_by_baseline(): Formatted analysis function which is used as afun in count_abnormal_by_baseline().

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

Note

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

  • If the baseline variable or analysis variable contains NA, it is expected that NA has been conveyed to na_level appropriately beforehand with df_explicit_na() or explicit_na().

See also

Relevant description function d_count_abnormal_by_baseline().

Examples 

df <- data.frame(
  USUBJID = as.character(c(1:6)),
  ANRIND = factor(c(rep("LOW", 4), "NORMAL", "HIGH")),
  BNRIND = factor(c("LOW", "NORMAL", "HIGH", NA, "LOW", "NORMAL"))
)
df <- df_explicit_na(df)

# Internal function - s_count_abnormal_by_baseline
if (FALSE) {
# Just for one abnormal level.
s_count_abnormal_by_baseline(df, .var = "ANRIND", abnormal = "HIGH")
}

# Internal function - a_count_abnormal_by_baseline
if (FALSE) {
# Use the Formatted Analysis function for `analyze()`. We need to ungroup `fraction` first
# so that the `rtables` formatting function `format_fraction()` can be applied correctly.
afun <- make_afun(a_count_abnormal_by_baseline, .ungroup_stats = "fraction")
afun(df, .var = "ANRIND", abnormal = "LOW")
}

# Layout creating function.
basic_table() %>%
  count_abnormal_by_baseline(var = "ANRIND", abnormal = c(High = "HIGH")) %>%
  build_table(df)
#>                                all obs  
#> ————————————————————————————————————————
#> High                                    
#>   Not high baseline status    1/4 (25%) 
#>   High baseline status           0/1    
#>   Total                      1/6 (16.7%)

# Passing of statistics function and formatting arguments.
df2 <- data.frame(
  ID = as.character(c(1, 2, 3, 4)),
  RANGE = factor(c("NORMAL", "LOW", "HIGH", "HIGH")),
  BLRANGE = factor(c("LOW", "HIGH", "HIGH", "NORMAL"))
)

basic_table() %>%
  count_abnormal_by_baseline(
    var = "RANGE",
    abnormal = c(Low = "LOW"),
    variables = list(id = "ID", baseline = "BLRANGE"),
    .formats = c(fraction = "xx / xx"),
    .indent_mods = c(fraction = 2L)
  ) %>%
  build_table(df2)
#>                                 all obs
#> ———————————————————————————————————————
#> Low                                    
#>       Not low baseline status    1 / 3 
#>       Low baseline status        0 / 1 
#>       Total                      1 / 4