Note: This vignette is illustrated with fake data. The dataset explored in this example should not be used to inform decision-making.
ready4use includes a number of tools for ingesting health economic model data from online repositories and forms part of the ready4 framework. Details of how to find compatible datasets are provided in another article.
Specify remote repositories
The Ready4useRepos
class can be used to specify details
of the data repositories used in your data management workflows.
Currently, the two types of repository that can be specified in a
Ready4useRepos
class are Dataverse datasets and GitHub
releases. Ready4useRepos
methods for download / upload
extend tools from the dataverse
and piggyback
packages.
X <- Ready4useRepos(dv_nm_1L_chr = "fakes",
dv_ds_nm_1L_chr = "https://doi.org/10.7910/DVN/HJXYKQ",
dv_server_1L_chr = "dataverse.harvard.edu",
gh_repo_1L_chr = "ready4-dev/ready4",
gh_tag_1L_chr = "Documentation_0.0")
Ingest data
To import objects that have been saved as RDS file format in data
repositories specified in an Ready4useRepos
instance, use
the ingest
method.
The ingest
method imports all RDS files in the specified
repositories unless you request a more targeted approach by supplying
the names of desired files to the fls_to_ingest_chr
argument. By default, the ingest
method transforms
X
into an object of class Ready4useRecord
,
which pairs the ingested data with metadata describing the ingested data
and their provenance.
If metadata are not required, we can simply ingest a list containing
the requested objects by supplying the metadata_1L_lgl = F
argument.
## Not run
# objects_ls <- ingest(X,
# fls_to_ingest_chr = c("ymh_clinical_tb","ymh_clinical_dict_r3"),
# metadata_1L_lgl = F)
If we specify just a single object name for ingest, then the
ingest
method returns just that object (instead of a list
containing that object).
## Not run
# ymh_clinical_tb <- ingest(X,
# fls_to_ingest_chr = c("ymh_clinical_tb"),
# metadata_1L_lgl = F)