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Patient Counts with Abnormal Range Values by Baseline Status

Source: R/abnormal_by_baseline.R
abnormal_by_baseline.Rd

[Stable]

Usage

d_count_abnormal_by_baseline(abnormal)

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

abnormal

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

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.

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

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

Details

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

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

Functions

  • d_count_abnormal_by_baseline(): Description Function that produces the labels for s_count_abnormal_by_baseline().

  • s_count_abnormal_by_baseline(): For a single abnormal level, produce a statistic fraction which is a named list with 3 elements: not_abnormal, abnormal and total. Each element contains a vector with num and denom counts of patients. Please note that 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().

  • a_count_abnormal_by_baseline(): Formatted Analysis function which can be further customized by calling rtables::make_afun() on it. It is used as afun in rtables::analyze().

  • count_abnormal_by_baseline(): Layout creating function which can be used for creating tables, which can take statistics function arguments and additional format arguments (see below).

Examples

d_count_abnormal_by_baseline("LOW")
#> $not_abnormal
#> [1] "Not low baseline status"
#> 
#> $abnormal
#> [1] "Low baseline status"
#> 
#> $total
#> [1] "Total"
#> 

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