dq_report_by: Generate a stratified full DQ report

In dataquieR: Data Quality in Epidemiological Research

Generate a stratified full DQ report

Description

Generate a stratified full DQ report

Usage

dq_report_by(
  study_data,
  meta_data = "item_level",
  meta_data_segment = "segment_level",
  meta_data_dataframe = "dataframe_level",
  meta_data_cross_item = "cross-item_level",
  label_col,
  meta_data_v2,
  meta_data_split = STUDY_SEGMENT,
  study_data_split,
  ...,
  output_dir = NULL,
  also_print = FALSE,
  disable_plotly = FALSE
)

Arguments

study_data	data.frame the data frame that contains the measurements
meta_data	data.frame the data frame that contains metadata attributes of study data
meta_data_segment	data.frame – optional: Segment level metadata
meta_data_dataframe	data.frame – optional: Data frame level metadata
meta_data_cross_item	data.frame – optional: Cross-item level metadata
label_col	variable attribute the name of the column in the metadata with labels of variables
meta_data_v2	character path to workbook like metadata file, see prep_load_workbook_like_file for details. ALL LOADED DATAFRAMES WILL BE PURGED, using prep_purge_data_frame_cache, if you specify meta_data_v2.
meta_data_split	variable attribute name of a metadata attribute to split the report in sections of variables, e.g. all blood- pressure. By default, reports are split by STUDY_SEGMENT if available.
study_data_split	variable Name of a study variable to stratify the report by, e.g. the study centers.
...	arguments to be passed through to dq_report or dq_report2
output_dir	character if given, the output is not returned but
also_print	logical if output_dir is not NULL, also create HTML output for each segment using print.dataquieR_resultset2(). written to the path output_dir
disable_plotly	logical do not use plotly, even if installed

Value

named list of named lists of dq_report2 reports or, if output_dir has been specified, invisible(NULL)

See Also

dq_report

Examples

## Not run:  # really long-running example.
prep_load_workbook_like_file("meta_data_v2")
rep <- dq_report_by("study_data", label_col =
  LABEL, study_data_split = "CENTER_0")
rep <- dq_report_by("study_data",
  label_col = LABEL, study_data_split = "CENTER_0",
  meta_data_split = NULL
)
unlink("/tmp/testRep/", force = TRUE, recursive = TRUE)
dq_report_by("study_data",
  label_col = LABEL, study_data_split = "CENTER_0",
  meta_data_split = STUDY_SEGMENT, output_dir = "/tmp/testRep"
)
unlink("/tmp/testRep/", force = TRUE, recursive = TRUE)
dq_report_by("study_data",
  label_col = LABEL, study_data_split = "CENTER_0",
  meta_data_split = NULL, output_dir = "/tmp/testRep"
)
dq_report_by("study_data",
  label_col = LABEL,
  meta_data_split = STUDY_SEGMENT, output_dir = "/tmp/testRep"
)
dq_report_by("study_data",
  label_col = LABEL,
  meta_data_split = STUDY_SEGMENT, output_dir = "/tmp/testRep",
  also_print = TRUE
)
dq_report_by(study_data = "study_data", meta_data_v2 = "meta_data_v2",
  advanced_options = list(dataquieR.study_data_cache_max = 0,
  dataquieR.study_data_cache_metrics = TRUE,
  dataquieR.study_data_cache_metrics_env = environment()),
  cores = NULL, dimensions = "int")
dq_report_by(study_data = "study_data", meta_data_v2 = "meta_data_v2",
  advanced_options = list(dataquieR.study_data_cache_max = 0),
  cores = NULL, dimensions = "int")

## End(Not run)

dataquieR documentation built on May 29, 2024, 7:18 a.m.