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Descriptive Statistics for Univariate Data with Optional Reference Comparison

Source: R/s_summary_diff.r
s_summary_diff.Rd

[Experimental]

Computes descriptive statistics for a single variable df[[.var]] using tern::s_summary(), which dispatches type-specific methods depending on the S3 class of the input (e.g., character, factor, logical, numeric).

Optionally, it computes a difference in means with confidence interval between df[[.var]] and .ref_group[[.var]] using s_diff_mean_ci(). This statistic is applicable only to numeric variables.

Usage

s_summary_diff(
  df,
  .var,
  .stats = NULL,
  .ref_group = NULL,
  .in_ref_col = FALSE,
  control = tern::control_analyze_vars(),
  ...
)

Arguments

df

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

.var

(character(1))
Name of the column in df containing the values for which statistics are computed. The variable type is handled by the corresponding methods of tern::s_summary(). The diff_mean_ci statistic is only valid when df[[.var]] is numeric.

.stats

(character or NULL)
Names of statistics to be computed. For numerical data, supported statistics are listed via tern::get_stats(method_groups = "analyze_vars_numeric", custom_stats_in = "diff_mean_ci"). If NULL, all available statistics for numerical data are computed.

.ref_group

(data.frame or vector)
the data corresponding to the reference group.

.in_ref_col

(logical)
TRUE when working with the reference level, FALSE otherwise.

control

(list)
List of control options passed to tern::s_summary(). If diff_mean_ci statistic is requested, control$conf_level specifies the confidence level used for the interval.

...

Additional arguments passed to tern::s_summary() and to s_diff_mean_ci() when diff_mean_ci is computed.

Value

A named list with the requested statistics.

Examples

df <- data.frame(
  USUBJID = c("X01", "X02", "X03", "X04", "X05"),
  TRT01A = rep("ARM_A", 5),
  PARAMCD = rep("SYSBP", 5),
  AVISIT = rep("Visit 1", 5),
  CHG = c(4, 1, -1, 9, -2)
)
df
#>   USUBJID TRT01A PARAMCD  AVISIT CHG
#> 1     X01  ARM_A   SYSBP Visit 1   4
#> 2     X02  ARM_A   SYSBP Visit 1   1
#> 3     X03  ARM_A   SYSBP Visit 1  -1
#> 4     X04  ARM_A   SYSBP Visit 1   9
#> 5     X05  ARM_A   SYSBP Visit 1  -2

rg <- data.frame(
  USUBJID = c("X06", "X07", "X08", "X09", "X10"),
  TRT01A = rep("Placebo", 5),
  PARAMCD = rep("SYSBP", 5),
  AVISIT = rep("Visit 1", 5),
  CHG = c(-2, 6, -2, 5, 2)
)
rg
#>   USUBJID  TRT01A PARAMCD  AVISIT CHG
#> 1     X06 Placebo   SYSBP Visit 1  -2
#> 2     X07 Placebo   SYSBP Visit 1   6
#> 3     X08 Placebo   SYSBP Visit 1  -2
#> 4     X09 Placebo   SYSBP Visit 1   5
#> 5     X10 Placebo   SYSBP Visit 1   2

.stats <- c("n", "mean_sd", "diff_mean_ci")

# With reference group.
s_summary_diff(df, "CHG", .stats, rg)
#> $n
#> n 
#> 5 
#> 
#> $mean_sd
#>     mean       sd 
#> 2.200000 4.438468 
#> 
#> $diff_mean_ci
#> diff_mean    ci_lwr    ci_upr 
#>  0.400000 -5.632096  6.432096 
#> attr(,"label")
#> [1] "Difference in Means + 95% CI"
#> 

# Using df as reference.
s_summary_diff(df, "CHG", .stats, df, .in_ref_col = TRUE)
#> $n
#> n 
#> 5 
#> 
#> $mean_sd
#>     mean       sd 
#> 2.200000 4.438468 
#> 
#> $diff_mean_ci
#> NULL
#>