Complete not quantified values — complete

complete_data() completes missing values related to the limits of quantification or detection.

Usage

complete_data(
  dat,
  LOD_method = NULL,
  LLOQ_method = NULL,
  ULOQ_method = NULL,
  LOD_type = "calc"
)

Arguments

dat: a raw_data object. Output of read_data() function.
LOD_method: a character string specifying the imputation method to be applied to < LOD values, or NULL to change these values to NA. Available methods are: halfmin, random, halflimit, limit, limit-0.2min and logspline.
LLOQ_method: a character string specifying the imputation method to be applied to < LLOQ values, or NULL if these values should not be imputed. Currently, the only available method is: limit.
ULOQ_method: a character string specifying the imputation method to be applied to > ULOQ values, or NULL if these values should not be imputed. Available methods are: limit, third quartile and scaled random.
LOD_type: a character string specifying which LOD type to use for imputing values. Possible values are "OP" and "calc".

Examples

path <- get_example_data("small_biocrates_example.xls")
dat <- read_data(path)
dat <- complete_data(dat)
#> Skipping < LOD imputation.
#> Skipping < LLOQ imputation.
#> Skipping > ULOQ imputation.