Rmonize (version 2.0.0)

pooled_harmonized_dataset_create: Generate a pooled harmonized dataset from a harmonized dossier

Description

Generates a pooled harmonized dataset from a harmonized dossier. The function has two arguments that can optionally be declared by the user (harmonized_col_dataset and harmonized_col_id). harmonized_col_dataset refers to the columns which contains name of each harmonized dataset. harmonized_col_id refers to the column in harmonized datasets which identifies unique combinations of observation/dataset. These two columns are added to ensure that there is always a unique entity identifier when datasets are pooled.

Usage

pooled_harmonized_dataset_create(
  harmonized_dossier,
  harmonized_col_dataset =
    attributes(harmonized_dossier)$`Rmonize::harmonized_col_dataset`,
  harmonized_col_id = attributes(harmonized_dossier)$`Rmonize::harmonized_col_id`,
  dataschema = attributes(harmonized_dossier)$`Rmonize::DataSchema`,
  data_proc_elem = attributes(harmonized_dossier)$`Rmonize::Data Processing Elements`
)

Value

A data frame containing the pooled harmonized dataset.

Arguments

harmonized_dossier

A list containing the harmonized dataset(s).

harmonized_col_dataset

A character string identifying the column to use for dataset names.

harmonized_col_id

A character string identifying the name of the column present in every dataset to use as a participant identifier.

dataschema

A DataSchema object.

data_proc_elem

A Data Processing Elements object.

Details

A harmonized dossier is a named list containing one or more data frames, which are harmonized datasets. A harmonized dossier is generally the product of applying processing to a dossier object The name of each harmonized dataset (data frame) is taken from the reference input dataset. A harmonized dossier also contains the DataSchema and Data Processing Elements used in processing as attributes.

A DataSchema is the list of core variables to generate across datasets and related metadata. A DataSchema object is a list of data frames with elements named 'Variables' (required) and 'Categories' (if any). The 'Variables' element must contain at least the name column, and the 'Categories' element must contain at least the variable and name columns to be usable in any function. In 'Variables' the name column must also have unique entries, and in 'Categories' the combination of variable and name columns must also be unique.

The Data Processing Elements specifies the input elements and processing algorithms to generate harmonized variables in the DataSchema formats. It is also contains metadata used to generate documentation of the processing. A Data Processing Elements object is a data frame with specific columns used in data processing: dataschema_variable, input_dataset, input_variables, Mlstr_harmo::rule_category and Mlstr_harmo::algorithm. To initiate processing, the first entry must be the creation of a harmonized primary identifier variable (e.g., participant unique ID).

Examples

{

# Use Rmonize_examples to run examples.
 
library(dplyr)

# Perform data processing
harmonized_dossier <- Rmonize_examples["harmonized_dossier"][[1]]

# create the pooled harmonized dataset from the harmonized dossier
pooled_harmonized_dataset <- pooled_harmonized_dataset_create(harmonized_dossier)
  
glimpse(pooled_harmonized_dataset)
  
}