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Create specification object for ADaM data sets of type occds

Source: R/adam_spec_occds.R
adam_spec_occds.Rd

Given a file containing a occds data set (e.g. admh or adcm), adam_spec_occds() will create a specification object for use in build_occds() to prepare the data to be used in machine learning. The main task is to collect the key columns for reshaping the data into wide format and prepare the data filter.

Usage

adam_spec_occds(
  file = NULL,
  data = NULL,
  id = "SUBJID",
  label = NULL,
  value = NULL,
  valuen = NULL,
  filter = NULL,
  count = TRUE,
  time = NULL,
  pre_study = FALSE,
  attach_data = FALSE
)

Arguments

file

the path of the sas(7bdat) or rds file to process, ignored if data is provided

data

tibble with the data in occds format for which the specification is created

id

name of id column to be kept and used for merge of data sets

label

name of the column that identifies the occurrence labels. Defaults to NULL, will be guessed if not set (see Details).

value

optional value column (e.g. AE severity). Defaults to NULL, which leads to an Y/N coding of the event.

valuen

optional numeric coding column for value. Defaults to NULL, ignored if value is NULL.

filter

character vector of filters to be applied to the bds data set. Individual filters will only be considered if the resulting data set has positive number of rows. Defaults to NULL.

count

boolean, defaults to FALSE.

time

name of the column that is used for time filtering (if required via pre_study argument). Defaults to NULL, will be guessed if not set (see Details).

pre_study

boolean. filter the data set to pre_study observations based on non-negative values in time

attach_data

boolean. attach the imported raw data in data slot of output object

Value

A list containing the following

file, md5

the name and md5 checksum, resp., of the file the generated spec is based upon

data

the raw data set if attach_data, NULL otherwise

data_info

a list containing the number of subjects nsubj and columns ncol in the data after applying filter

type

character string occds, generally giving the type of ADaM data set processed (adsl/bds/occds)

filter

subset of filter that yields valid and non-empty result when applied individually (using check_filter())

id

passing unchanged input

label, value, valuen

names of the key columns to be used in build_occds() for reshaping

spec_id

character string, generally the name of the domain

dict

a tibble with unique combinations within the param and label column (if present in the data set) to be used as a data dictionary

Details

For file names 'adae.sas7bdat', 'adcm.sas7bdat' and 'admh.sas7bdat', values for arguments label will be guessed if not provided, the same goes for time if pre_study=TRUE. Please refer to adam_guess() for details on guessing procedure. Function will exit if label is neither provided nor can be guessed. If a pre-study filter is requested, the function will escape if time is neither provided nor can be guessed. Note that the original values in the label column will end up being the parameter labels, not the parameters in the ML feature matrix. These might be modified later using make.names() or the like in prepare_ml().

Authors

Maike Ahrens (ahrensmaike), Sebastian Voss (svoss09)