View source: R/02-harmo_process_harmonization.R
harmo_process | R Documentation |
Reads a DataSchema and Data Processing Elements to generate a
harmonized dossier from input dataset(s) in a dossier and associated
metadata. The function
has one argument that can optionally be declared by the user
(unique_col_dataset
). It refers to the columns which contains name of
each harmonized dataset. These two columns are added to ensure that there
is always a unique entity identifier when datasets are pooled.
harmo_process(
object,
dataschema = attributes(object)$`Rmonize::DataSchema`,
data_proc_elem = attributes(object)$`Rmonize::Data Processing Elements`,
harmonized_col_dataset = attributes(object)$`Rmonize::harmonized_col_dataset`,
harmonized_col_id = attributes(object)$`Rmonize::harmonized_col_id`,
.debug = FALSE
)
object |
Data frame(s) or list of data frame(s) containing input dataset(s). |
dataschema |
A DataSchema object. |
data_proc_elem |
A Data Processing Elements object. |
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. |
.debug |
Allow user to test the inputs before processing harmonization. |
A dossier is a named list containing one or more data frames, which are
input datasets. The name of each data frame in the dossier will be used as
the name of the associated harmonized dataset produced by harmo_process()
.
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).
A list of data frame(s) containing harmonized dataset(s). The DataSchema and Data Processing Elements are preserved as attributes of the harmonized dossier.
# Use Rmonize_examples to run examples.
library(dplyr)
library(stringr)
library(lubridate)
# Perform data processing
dossier <- Rmonize_examples[str_detect(names(Rmonize_examples),"input_dataset_study")]
names(dossier) <- str_remove(names(dossier), "input_")
dataschema <- Rmonize_examples$`DataSchema`
data_proc_elem <- Rmonize_examples$`Data_Processing_Elements_no_errors`
harmonized_dossier <- harmo_process(
dossier,
dataschema,
data_proc_elem,
harmonized_col_dataset = 'adm_study_id')
glimpse(harmonized_dossier$dataset_study1)
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