R: Data Quality in Epidemiological Research

# Data Quality in Epidemiological Research

## Documentation for package ‘dataquieR’ version 2.8.7

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

A C D E F G H I J K L M N O P R S T U V W misc

## -- A --

acc_cat_distributions | Plots and checks for distributions for categorical variables
acc_distributions | Plots and checks for distributions
acc_distributions_ecdf | ECDF plots for distribution checks
acc_distributions_loc | Plots and checks for distributions - Location
acc_distributions_only | Plots and checks for distributions - only
acc_distributions_prop | Plots and checks for distributions - Proportion
acc_end_digits | Extension of acc_shape_or_scale to examine uniform distributions of end digits
acc_loess | Smoothes and plots adjusted longitudinal measurements and longitudinal trends from logistic regression models
acc_mahalanobis | Calculate and plot Mahalanobis distances for social science indices
acc_margins | Estimate marginal means, see emmeans::emmeans
acc_multivariate_outlier | Calculate and plot Mahalanobis distances
acc_robust_univariate_outlier | Identify univariate outliers by four different approaches
acc_shape_or_scale | Compare observed versus expected distributions
acc_univariate_outlier | Identify univariate outliers by four different approaches
acc_varcomp | Utility function to compute model-based ICC depending on the (statistical) data type
as.character.interval | 'as.character' implementation for the class 'interval'
as.data.frame.dataquieR_resultset | Convert a full 'dataquieR' report to a 'data.frame'
as.list.dataquieR_resultset | Convert a full 'dataquieR' report to a 'list'
as.list.dataquieR_resultset2 | inefficient way to convert a report to a list. try 'prep_set_backend()'
ASSOCIATION_DIRECTION | Cross-item level metadata attribute name
ASSOCIATION_FORM | Cross-item level metadata attribute name
ASSOCIATION_METRIC | Cross-item level metadata attribute name
ASSOCIATION_RANGE | Cross-item level metadata attribute name

## -- C --

cash-.dataquieR_resultset2 | Access single results from a dataquieR_resultset2 report
cash-set-.dataquieR_resultset2.Rd | Write single results from a dataquieR_resultset2 report
cause_label_df | Data frame with labels for missing- and jump-codes #' Metadata about value and missing codes
CHECK_ID | Cross-item level metadata attribute name
CHECK_LABEL | Cross-item level metadata attribute name
check_table | Data frame with contradiction rules
CODE_CLASS | Data frame with labels for missing- and jump-codes #' Metadata about value and missing codes
CODE_CLASSES | types of value codes
CODE_INTERPRET | Data frame with labels for missing- and jump-codes #' Metadata about value and missing codes
CODE_LABEL | Data frame with labels for missing- and jump-codes #' Metadata about value and missing codes
CODE_LIST_TABLE | Default Name of the Table featuring Code Lists
CODE_ORDER | Only existence is checked, order not yet used
CODE_VALUE | Data frame with labels for missing- and jump-codes #' Metadata about value and missing codes
COMPATIBILITY | Requirement levels of certain metadata columns
COMPUTATION_RULE | Cross-item level metadata attribute name
COMPUTED_VARIABLE_ROLE | Well-known metadata column names, names of metadata columns
COMPUTED_VARIABLE_ROLES | 'SSI' related Cross-item level metadata attribute names Computed Variable roles can be one of the following:
com_item_missingness | Summarize missingness columnwise (in variable)
com_qualified_item_missingness | Compute Indicators for Qualified Item Missingness
com_qualified_segment_missingness | Compute Indicators for Qualified Segment Missingness
com_segment_missingness | Summarizes missingness for individuals in specific segments
com_unit_missingness | Counts all individuals with no measurements at all
CONTRADICTIONS | Well-known metadata column names, names of metadata columns
contradiction_functions_descriptions | description of the contradiction functions
CONTRADICTION_TERM | Cross-item level metadata attribute name
CONTRADICTION_TYPE | Cross-item level metadata attribute name
con_contradictions | Checks user-defined contradictions in study data
con_contradictions_redcap | Checks user-defined contradictions in study data
con_inadmissible_categorical | Detects variable levels not specified in metadata
con_inadmissible_vocabulary | Detects variable levels not specified in standardized vocabulary
con_limit_deviations | Detects variable values exceeding limits defined in metadata
CO_VARS | Well-known metadata column names, names of metadata columns

## -- D --

DATAFRAMES | Well-known metadata column names, names of metadata columns
dataquieR.acc_loess.exclude_constant_subgroups | Exclude subgroups with constant values from LOESS figure
dataquieR.acc_loess.mark_time_points | Display time-points in LOESS plots
dataquieR.acc_loess.min_bw | Lower limit for the LOESS bandwidth
dataquieR.acc_loess.min_proportion | Lower limit for the proportion of cases or controls to create a smoothed time trend figure
dataquieR.acc_loess.plot_format | default for Plot-Format in 'acc_loess()'
dataquieR.acc_loess.plot_observations | Display observations in LOESS plots
dataquieR.acc_margins_num | Include number of observations for each level of the grouping variable in the 'margins' figure
dataquieR.acc_margins_sort | Sort levels of the grouping variable in the 'margins' figures
dataquieR.acc_multivariate_outlier.scale | Apply min-max scaling in parallel coordinates figure to inspect multivariate outliers
dataquieR.applicability_problem | An exception class assigned for exceptions caused by trying to apply a non-applicable indicator function
dataquieR.col_con_con_empirical | Color for empirical contradictions
dataquieR.col_con_con_logical | Color for logical contradictions
dataquieR.CONDITIONS_LEVEL_TRHESHOLD | Log Level
dataquieR.CONDITIONS_WITH_STACKTRACE | Add stack-trace in condition messages (to be deprecated)
dataquieR.convert_to_list_for_lapply | If report uses a 'storr' back-end, do not convert to base-list
dataquieR.debug | Call 'browser()' on errors
dataquieR.des_summary_hard_lim_remove | Removal of hard limits from data before calculating descriptive statistics.
dataquieR.dontwrapresults | Disable automatic post-processing of 'dataquieR' function results
dataquieR.droplevels_ReportSummaryTable | Show also unused levels in heatmaps
dataquieR.dt_adjust | character Adjust data types according to metadata
dataquieR.ELEMENT_MISSMATCH_CHECKTYPE | Metadata describes more than the current study data
dataquieR.ERRORS_WITH_CALLER | Set caller for error conditions (to be deprecated)
dataquieR.fix_column_type_on_read | Try to avoid fallback to string columns when reading files
dataquieR.flip_mode | Flip-Mode to Use for figures
dataquieR.force_item_specific_missing_codes | Converting MISSING_LIST/JUMP_LIST to a MISSING_LIST_TABLE create on list per item
dataquieR.force_label_col | Control, how the 'label_col' argument is used.
dataquieR.GAM_for_LOESS | Enable to switch to a general additive model instead of LOESS
dataquieR.grading_formats | Name of the data.frame featuring a format for grading-values
dataquieR.grading_rulesets | Name of the data.frame featuring GRADING_RULESET
dataquieR.guess_character | For metadata guessing, try to guess DATA_TYPE from the data values
dataquieR.guess_missing_codes | Control, if 'dataquieR' tries to guess missing-codes from the study data in absence of metadata
dataquieR.ignore_empty_vars | character remove variables with only empty values
dataquieR.intrinsic_applicability_problem | An exception class assigned for exceptions caused by trying to apply a non-applicable indicator function, which is not caused by deficient metadata
dataquieR.lang | Language-Suffix for metadata Label-Columns
dataquieR.lazy_plots | character plots realized lazy
dataquieR.lazy_plots_cache | character cache realizations
dataquieR.lazy_plots_gg_compatibility | character be as compatible with 'ggplot2' objects as possible
dataquieR.locale | character default language for type conversion
dataquieR.MAHALANOBIS_THRESHOLD | Default availability of Mahalanobis based multivariate outlier checks in reports
dataquieR.max_cat_resp_var_levels_in_plot | Maximum number of levels of the categorical response variable shown individually in figures
dataquieR.max_group_var_levels_in_plot | Maximum number of levels of the grouping variable shown individually in figures
dataquieR.max_group_var_levels_with_violins | Maximum number of levels of the grouping variable shown with individual histograms ('violins') in 'margins' figures
dataquieR.MAX_LABEL_LEN | Maximum length for variable labels LABEL
dataquieR.MAX_LONG_LABEL_LEN | Maximum length for long variable labels LONG_LABEL
dataquieR.MAX_VALUE_LABEL_LEN | Maximum length for value labels
dataquieR.MESSAGES_WITH_CALLER | Set caller for message conditions (to be deprecated)
dataquieR.min_obs_per_group_var_in_plot | Minimum number of observations per grouping variable that is required to include an individual level of the grouping variable in a figure
dataquieR.min_time_points_for_cat_resp_var | Minimum number of data points to create a time course plot for an individual level of a categorical response variable
dataquieR.MULTIVARIATE_OUTLIER_CHECK | Default availability of multivariate outlier checks in reports
dataquieR.non_disclosure | Remove all observation-level-real-data from reports
dataquieR.old_factor_handling | character use the old handling of study data already featuring factors
dataquieR.old_type_adjust | character use the old type conversion code (slower)
dataquieR.precomputeStudyData | Pre-compute different curation levels of study data
dataquieR.print_block_load_factor | numeric
dataquieR.progress_fkt_default | function to call on progress increase
dataquieR.progress_msg_fkt_default | function to call on progress message update
dataquieR.resume_checkpoint | If result already exists in a 'storr' back-end, re-use it
dataquieR.resume_print | If output folder is not empty, try to resume stopped 'print()'
dataquieR.scale_level_heuristics_control_binaryrecodelimit | Number of levels to consider a variable ordinal in absence of SCALE_LEVEL
dataquieR.scale_level_heuristics_control_metriclevels | Number of levels to consider a variable metric in absence of SCALE_LEVEL
dataquieR.study_data_cache_max | Maximum size of cache for curated study data
dataquieR.study_data_cache_metrics | Collect metrics on cache usage of study data cache
dataquieR.study_data_cache_metrics_env | environment for storing metrics on the study data cache
dataquieR.study_data_cache_metrics_env_default | Default space for some metrics during report computation
dataquieR.study_data_cache_quick_fill | Control the pre-computation of curation levels of study data
dataquieR.study_data_colnames_case_sensitive | character Are column names in study data considered case-sensitive for mapping
dataquieR.testdebug | Disable all interactively used metadata-based function argument provision
dataquieR.traceback | Include full trace-back in captured conditions
dataquieR.type_adjust_parallel | character try to do type adjustments in parallel only, if 'dq_report2()' was called with 'cores = 2' or higher.
dataquieR.VALUE_LABELS_htmlescaped | Assume, all VALUE_LABELS are HTML escaped
dataquieR.WARNINGS_WITH_CALLER | Set caller for warning conditions (to be deprecated)
dataquieR_result | Print a dataquieR result returned by dq_report2
dataquieR_resultset | Internal constructor for the internal class dataquieR_resultset.
dataquieR_resultset2 | Class dataquieR_resultset2.
dataquieR_resultset2-class | Class dataquieR_resultset2.
dataquieR_resultset_verify | Verify an object of class dataquieR_resultset
DATA_ENTRY_TYPE | Well-known metadata column names, names of metadata columns
DATA_PREPARATION | Cross-item level metadata attribute name
DATA_TYPE | Well-known metadata column names, names of metadata columns
DATA_TYPES | Data Types
DATA_TYPES_OF_R_TYPE | All available data types, mapped from their respective R types
DATETIME | Data Types
datetime | Data Types
DECIMALS | Well-known metadata column names, names of metadata columns
des_scatterplot_matrix | Compute Pairwise Correlations
des_summary | Compute Descriptive Statistics
des_summary_categorical | Compute Descriptive Statistics - categorical variables
des_summary_continuous | Compute Descriptive Statistics - continuous variables
DETECTION_LIMITS | Well-known metadata column names, names of metadata columns
DETECTION_LIMIT_LOW | Well-known metadata column names, names of metadata columns
DETECTION_LIMIT_UP | Well-known metadata column names, names of metadata columns
DF_CODE | Data frame level metadata attribute name
DF_ELEMENT_COUNT | Data frame level metadata attribute name
DF_ID_REF_TABLE | Data frame level metadata attribute name
DF_ID_VARS | Data frame level metadata attribute name
DF_NAME | Data frame level metadata attribute name
DF_RECORD_CHECK | Data frame level metadata attribute name
DF_RECORD_COUNT | Data frame level metadata attribute name
DF_UNIQUE_ID | Data frame level metadata attribute name
DF_UNIQUE_ROWS | Data frame level metadata attribute name
dim.dataquieR_resultset2 | Get the dimensions of a 'dq_report2' result
dimensions | Names of DQ dimensions
dimnames.dataquieR_resultset2 | Names of a 'dataquieR' report object (v2.0)
dims | Dimension Titles for Prefixes
DISTRIBUTION | Well-known metadata column names, names of metadata columns
DISTRIBUTIONS | All available probability distributions for acc_shape_or_scale
dq_lazy_ggplot_methods | S3/S7 methods for lazy ggplot objects
dq_report | Generate a full DQ report
dq_report2 | Generate a full DQ report, v2
dq_report_by | Generate a stratified full DQ report
droplevels.ReportSummaryTable | Remove unused levels from 'ReportSummaryTable'

## -- E --

ENCODING | Well-known metadata column names, names of metadata columns
END_DIGIT_CHECK | Well-known metadata column names, names of metadata columns
enum | Data Types
EXTENDED_DATA_TYPE | Well-known metadata column names, names of metadata columns

## -- F --

FLOAT | Data Types
float | Data Types

## -- G --

ggplotGrob.dq_lazy_ggplot | S3/S7 methods for lazy ggplot objects
ggplotGrob.dq_lazy_ggplot_s7 | S3/S7 methods for lazy ggplot objects
ggplotly.dq_lazy_ggplot | S3/S7 methods for lazy ggplot objects
ggplotly.dq_lazy_ggplot_s7 | S3/S7 methods for lazy ggplot objects
GOLDSTANDARD | Cross-item level metadata attribute name
GRADING_RULESET | Well-known metadata column names, names of metadata columns
grid.draw.util_pairs_ggplot_panels | 'grid.draw' method for 'util_pairs_ggplot_panels' objects
GROUP_VAR_DEVICE | Well-known metadata column names, names of metadata columns
GROUP_VAR_OBSERVER | Well-known metadata column names, names of metadata columns

## -- H --

HARD_LIMITS | Well-known metadata column names, names of metadata columns
HARD_LIMIT_LOW | Well-known metadata column names, names of metadata columns
HARD_LIMIT_UP | Well-known metadata column names, names of metadata columns
html_dependency_clipboard | HTML Dependency for report headers in 'clipboard'
html_dependency_dataquieR | HTML Dependency for 'dataquieR'
html_dependency_jspdf | HTML dependency for 'jsPDF'
html_dependency_report_dt | HTML Dependency for report headers in 'DT::datatable'
html_dependency_tippy | HTML Dependency for 'tippy'
html_dependency_vert_dt | HTML Dependency for vertical headers in 'DT::datatable'

## -- I --

INCL_HARD_LIMIT_LOW | Well-known metadata column names, names of metadata columns
INCL_HARD_LIMIT_UP | Well-known metadata column names, names of metadata columns
INCL_LOCATION_LIMIT_LOW | Well-known metadata column names, names of metadata columns
INCL_LOCATION_LIMIT_UP | Well-known metadata column names, names of metadata columns
INCL_PROPORTION_LIMIT_LOW | Well-known metadata column names, names of metadata columns
INCL_PROPORTION_LIMIT_UP | Well-known metadata column names, names of metadata columns
INCL_SOFT_LIMIT_LOW | Well-known metadata column names, names of metadata columns
INCL_SOFT_LIMIT_UP | Well-known metadata column names, names of metadata columns
INTEGER | Data Types
integer | Data Types
int_all_datastructure_dataframe | Wrapper function to check for studies data structure
int_all_datastructure_segment | Wrapper function to check for segment data structure
int_datatype_matrix | Check declared data types of metadata in study data
int_duplicate_content | Check for duplicated content
int_duplicate_ids | Check for duplicated IDs
int_encoding_errors | Encoding Errors
int_part_vars_structure | Detect Expected Observations
int_sts_element_dataframe | Determine missing and/or superfluous data elements
int_sts_element_segment | Checks for element set
int_unexp_elements | Check for unexpected data element count
int_unexp_records_dataframe | Check for unexpected data record count at the data frame level
int_unexp_records_segment | Check for unexpected data record count within segments
int_unexp_records_set | Check for unexpected data record set
IRV | Cross-item level metadata attribute name

## -- J --

JUMP_LIST | Well-known metadata column names, names of metadata columns

## -- K --

KEY_DATETIME | Well-known metadata column names, names of metadata columns
KEY_DEVICE | Well-known metadata column names, names of metadata columns
KEY_OBSERVER | Well-known metadata column names, names of metadata columns
KEY_STUDY_SEGMENT | Well-known metadata column names, names of metadata columns

## -- L --

LABEL | Well-known metadata column names, names of metadata columns
LOCATION_LIMIT_LOW | Well-known metadata column names, names of metadata columns
LOCATION_LIMIT_UP | Well-known metadata column names, names of metadata columns
LOCATION_METRIC | Well-known metadata column names, names of metadata columns
LOCATION_RANGE | Well-known metadata column names, names of metadata columns
LONG_LABEL | Well-known metadata column names, names of metadata columns

## -- M --

MAHALANOBIS_THRESHOLD | Cross-item level metadata attribute name
MAXIMUM_LONG_STRING | Cross-item level metadata attribute name
meta_data | Data frame with metadata about the study data on variable level
meta_data_computation | Well known columns on the 'item_computation_level' sheet
meta_data_cross | Well known columns on the 'cross-item_level' sheet
meta_data_dataframe | Well known columns on the 'meta_data_dataframe' sheet
meta_data_segment | Well known columns on the 'meta_data_segment' sheet
MISSING_LIST | Well-known metadata column names, names of metadata columns
MISSING_LIST_TABLE | Well-known metadata column names, names of metadata columns
missing_matchtable | Data frame with labels for missing- and jump-codes #' Metadata about value and missing codes
MISS_RESP | Cross-item level metadata attribute name
MULTIVARIATE_OUTLIER_CHECK | Cross-item level metadata attribute name
MULTIVARIATE_OUTLIER_CHECKTYPE | Cross-item level metadata attribute name

## -- N --

nres | return the number of result slots in a report
numeric | Data Types
N_RULES | Well-known metadata column names, names of metadata columns

## -- O --

OPTIONAL | Requirement levels of certain metadata columns

## -- P --

PART_VAR | Well-known metadata column names, names of metadata columns
pipeline_recursive_result | Convert a pipeline result data frame to named encapsulated lists
pipeline_vectorized | Call (nearly) one "Accuracy" function with many parameterizations at once automatically
plot.dataquieR_summary | Plot a 'dataquieR' summary
plotly_build.dq_lazy_ggplot | S3/S7 methods for lazy ggplot objects
plotly_build.dq_lazy_ggplot_s7 | S3/S7 methods for lazy ggplot objects
prep_acc_distributions_with_ecdf | Utility function to plot a combined figure for distribution checks
prep_add_cause_label_df | Convert missing codes in metadata format v1.0 and a missing-cause-table to v2.0 missing list / jump list assignments
prep_add_computed_variables | Insert missing codes for 'NA's based on rules
prep_add_data_frames | Add data frames to the pre-loaded / cache data frame environment
prep_add_missing_codes | Insert missing codes for 'NA's based on rules
prep_add_to_meta | Support function to augment metadata during data quality reporting
prep_apply_coding | Re-Code labels with their respective codes according to the 'meta_data'
prep_check_for_dataquieR_updates | Check for package updates
prep_check_meta_data_dataframe | Verify and normalize metadata on data frame level
prep_check_meta_data_segment | Verify and normalize metadata on segment level
prep_check_meta_names | Checks the validity of metadata w.r.t. the provided column names
prep_clean_labels | Support function to scan variable labels for applicability
prep_combine_report_summaries | Combine two report summaries
prep_compare_meta_with_study | Verify item-level metadata
prep_create_meta | Support function to create data.frames of metadata
prep_create_meta_data_file | Instantiate a new metadata file
prep_create_storr_factory | Create a factory function for 'storr' objects for backing a dataquieR_resultset2
prep_datatype_from_data | Get data types from data
prep_deparse_assignments | Convert two vectors from a code-value-table to a key-value list
prep_dq_data_type_of | Get the dataquieR 'DATA_TYPE' of 'x'
prep_expand_codes | Expand code labels across variables
prep_extract_cause_label_df | Extract all missing/jump codes from metadata and export a cause-label-data-frame
prep_extract_classes_by_functions | Extract old function based summary from data quality results
prep_extract_summary | Extract summary from data quality results
prep_extract_summary.dataquieR_result | Extract report summary from reports
prep_extract_summary.dataquieR_resultset2 | Extract report summary from reports
prep_fix_meta_id_dups | Fix metadata duplicates
prep_get_data_frame | Read data from files/URLs
prep_get_labels | Fetch a label for a variable based on its purpose
prep_get_study_data_segment | Get data frame for a given segment
prep_get_user_name | Return the logged-in User's Full Name
prep_guess_encoding | Guess encoding of text or text files
prep_link_escape | Prepare a label as part of a link for 'RMD' files
prep_list_dataframes | List Loaded Data Frames
prep_list_voc | All valid voc: vocabularies
prep_load_folder_with_metadata | Pre-load a folder with named (usually more than) one table(s)
prep_load_report | Load a 'dq_report2'
prep_load_report_from_backend | Load a report from a back-end
prep_load_workbook_like_file | Pre-load a file with named (usually more than) one table(s)
prep_map_labels | Support function to allocate labels to variables
prep_merge_study_data | Merge a list of study data frames to one (sparse) study data frame
prep_meta_data_v1_to_item_level_meta_data | Convert item-level metadata from v1.0 to v2.0
prep_min_obs_level | Support function to identify the levels of a process variable with minimum number of observations
prep_open_in_excel | Open a data frame in Excel
prep_pmap | Support function for a parallel 'pmap'
prep_prepare_dataframes | Prepare and verify study data with metadata
prep_purge_data_frame_cache | Clear data frame cache
prep_realize_ggplot | Materialize a lazy 'ggplot'
prep_remove_from_cache | Remove a specified element from the data frame cache
prep_render_pie_chart_from_summaryclasses_ggplot2 | Create a 'ggplot2' pie chart
prep_render_pie_chart_from_summaryclasses_plotly | Create a 'plotly' pie chart
prep_robust_guess_data_type | Guess the data type of a vector
prep_save_report | Save a 'dq_report2'
prep_scalelevel_from_data_and_metadata | Heuristics to amend a SCALE_LEVEL column and a UNIT column in the metadata
prep_set_backend | Change the back-end of a report
prep_study2meta | Guess a metadata data frame from study data.
prep_summary_to_classes | Classify metrics from a report summary table
prep_title_escape | Prepare a label as part of a title text for 'RMD' files
prep_undisclose | Remove data disclosing details
prep_unsplit_val_tabs | Combine all missing and value lists to one big table
prep_valuelabels_from_data | Get value labels from data
print.dataquieR_result | Print a dataquieR result returned by dq_report2
print.dataquieR_resultset | Generate a RMarkdown-based report from a dataquieR report
print.dataquieR_resultset2 | Generate a HTML-based report from a dataquieR report
print.dataquieR_summary | Print a 'dataquieR' summary
print.DataSlot | Print a 'DataSlot' object
print.interval | print implementation for the class 'interval'
print.list | print a list of 'dataquieR_result' objects
print.master_result | Print a 'master_result' object
print.numeric_with_unit | Print a number with unit
print.ReportSummaryTable | print implementation for the class 'ReportSummaryTable'
print.Slot | Print a 'Slot' object
print.StudyDataSlot | Print a 'StudyDataSlot' object
print.TableSlot | Print a 'TableSlot' object
print.util_pairs_ggplot_panels | Print method for 'util_pairs_ggplot_panels' objects
progress_init_fkt | function to call on progress initialization
PROPORTION_LIMIT_LOW | Well-known metadata column names, names of metadata columns
PROPORTION_LIMIT_UP | Well-known metadata column names, names of metadata columns
PROPORTION_RANGE | Well-known metadata column names, names of metadata columns
pro_applicability_matrix | Check applicability of DQ functions on study data

## -- R --

rbind.ReportSummaryTable | Combine 'ReportSummaryTable' outputs
RECODE_CASES | Well-known metadata column names, names of metadata columns
RECODE_CONTROL | Well-known metadata column names, names of metadata columns
RECOMMENDED | Requirement levels of certain metadata columns
RELCOMPL_SPEED | Cross-item level metadata attribute name
REL_VAL | Cross-item level metadata attribute name
REQUIRED | Requirement levels of certain metadata columns
resnames | Return names of result slots (e.g., 3rd dimension of dataquieR results)
resnames.dataquieR_resultset2 | Return names of result slots (e.g., 3rd dimension of dataquieR results)
RESPT_PER_ITEM | Cross-item level metadata attribute name
RULE | Cross-item level metadata attribute name

## -- S --

SCALE_ACRONYM | Cross-item level metadata attribute name TODO
SCALE_LEVEL | Well-known metadata column names, names of metadata columns
SCALE_LEVELS | Scale Levels
SCALE_NAME | Cross-item level metadata attribute name TODO
SEGMENT_ID_REF_TABLE | Segment level metadata attribute name
SEGMENT_ID_TABLE | Deprecated segment level metadata attribute name
SEGMENT_ID_VARS | Segment level metadata attribute name
SEGMENT_MISS | Segment level metadata attribute name
SEGMENT_PART_VARS | Segment level metadata attribute name
SEGMENT_RECORD_CHECK | Segment level metadata attribute name
SEGMENT_RECORD_COUNT | Segment level metadata attribute name
SEGMENT_UNIQUE_ID | Segment level metadata attribute name
SEGMENT_UNIQUE_ROWS | Segment level metadata attribute name
set | Data Types
SOFT_LIMITS | Well-known metadata column names, names of metadata columns
SOFT_LIMIT_LOW | Well-known metadata column names, names of metadata columns
SOFT_LIMIT_UP | Well-known metadata column names, names of metadata columns
SPLIT_CHAR | Character used by default as a separator in metadata such as missing codes
STANDARDIZED_VOCABULARY_TABLE | Well-known metadata column names, names of metadata columns
STRING | Data Types
string | Data Types
study_data | Data frame with the study data whose quality is being assessed
STUDY_SEGMENT | Well-known metadata column names, names of metadata columns
summary.dataquieR_resultset | Summarize a dataquieR report
summary.dataquieR_resultset2 | Generate a report summary table

## -- T --

TECHNICAL | Requirement levels of certain metadata columns
TIME | Data Types
time | Data Types
TIME_VAR | Well-known metadata column names, names of metadata columns
TIME_VAR_END | Well-known metadata column names, names of metadata columns
TOTRESPT | Cross-item level metadata attribute name

## -- U --

UNIT | Well-known metadata column names, names of metadata columns
UNITS | Valid unit symbols according to 'units::valid_udunits()'
UNIT_IS_COUNT | Is a unit a count according to 'units::valid_udunits()'
UNIT_PREFIXES | Valid unit prefixes according to 'units::valid_udunits_prefixes()'
UNIT_PREFIX_FACTORS | Factors related to unit prefixes 'units::valid_udunits_prefixes()'
UNIT_SOURCES | Maturity stage of a unit according to 'units::valid_udunits()'
UNIVARIATE_OUTLIER_CHECKTYPE | Well-known metadata column names, names of metadata columns
UNKNOWN | Requirement levels of certain metadata columns

## -- V --

value/missing-lists | Data frame with labels for missing- and jump-codes #' Metadata about value and missing codes
VALUE_LABELS | Well-known metadata column names, names of metadata columns
VALUE_LABEL_TABLE | Well-known metadata column names, names of metadata columns
value_label_table | Data frame with labels for missing- and jump-codes #' Metadata about value and missing codes
VARATT_REQUIRE_LEVELS | Requirement levels of certain metadata columns
variable | Data Types
variable attribute | Well-known metadata column names, names of metadata columns
variable list | Data Types
variable roles | Variable roles can be one of the following:
VARIABLE_LIST | Cross-item level metadata attribute name
VARIABLE_LIST_ORDER | Cross-item level metadata attribute name TODO internal use, only
VARIABLE_ORDER | Well-known metadata column names, names of metadata columns
VARIABLE_ROLE | Well-known metadata column names, names of metadata columns
VARIABLE_ROLES | Variable roles can be one of the following:
VAR_NAMES | Well-known metadata column names, names of metadata columns

## -- W --

WELL_KNOWN_META_VARIABLE_NAMES | Well-known metadata column names, names of metadata columns

## -- misc --

$.dataquieR_resultset2 | Access single results from a dataquieR_resultset2 report
$<-.dataquieR_resultset2 | Write single results from a dataquieR_resultset2 report
%%.numeric_with_unit | Operator caring for units
%/%.numeric_with_unit | Operator caring for units
*.numeric_with_unit | Operator caring for units
+.numeric_with_unit | Operator caring for units
-.numeric_with_unit | Operator caring for units
.dataquieR_resultset2 | Class dataquieR_resultset2.
/.numeric_with_unit | Operator caring for units
[.dataquieR_resultset2 | Get a subset of a 'dataquieR' 'dq_report2' report
[<-.dataquieR_resultset2 | Write to a report
[[.dataquieR_resultset2 | Get a single result from a dataquieR 2 report
[[<-.dataquieR_resultset2 | Set a single result from a dataquieR 2 report
^.numeric_with_unit | Operator caring for units