imputation_rule {tern} | R Documentation |
Apply 1/3 or 1/2 imputation rule to data
Description
Usage
imputation_rule(
df,
x_stats,
stat,
imp_rule,
post = FALSE,
avalcat_var = "AVALCAT1"
)
Arguments
df |
(data.frame ) data set containing all analysis variables.
|
x_stats |
(named list ) a named list of statistics, typically the results of s_summary() .
|
stat |
(string ) statistic to return the value/NA level of according to the imputation
rule applied.
|
imp_rule |
(string ) imputation rule setting. Set to "1/3" to implement 1/3 imputation
rule or "1/2" to implement 1/2 imputation rule.
|
post |
(flag ) whether the data corresponds to a post-dose time-point (defaults to FALSE ).
This parameter is only used when imp_rule is set to "1/3" .
|
avalcat_var |
(string ) name of variable that indicates whether a row in df corresponds
to an analysis value in category "BLQ" , "LTR" , "<PCLLOQ" , or none of the above
(defaults to "AVALCAT1" ). Variable avalcat_var must be present in df .
|
Value
A list
containing statistic value (val
) and NA level (na_str
) that should be displayed
according to the specified imputation rule.
See Also
analyze_vars_in_cols()
where this function can be implemented by setting the imp_rule
argument.
Examples
set.seed(1)
df <- data.frame(
AVAL = runif(50, 0, 1),
AVALCAT1 = sample(c(1, "BLQ"), 50, replace = TRUE)
)
x_stats <- s_summary(df$AVAL)
imputation_rule(df, x_stats, "max", "1/3")
imputation_rule(df, x_stats, "geom_mean", "1/3")
imputation_rule(df, x_stats, "mean", "1/2")
[Package
tern version 0.9.5
Index]