A C D E F G H I J K L M N O P R S T U V W misc
| 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_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.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 | 
| 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 | 
| 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 | 
| 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.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.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.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_missing_codes | Control, if 'dataquieR' tries to guess missing-codes from the study data in absence of metadata | 
| dataquieR.lang | Language-Suffix for metadata Label-Columns | 
| 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 | 
| 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.MULTIVARIATE_OUTLIER_CHECK | Default availability of multivariate outlier checks in reports | 
| dataquieR.non_disclosure | Remove all observation-level-real-data from reports | 
| dataquieR.progress_fkt | function to call on progress increase | 
| dataquieR.progress_msg_fkt | function to call on progress message update | 
| 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.testdebug | Disable all interactively used metadata-based function argument provision | 
| 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_report | Generate a full DQ report | 
| dq_report2 | Generate a full DQ report, v2 | 
| dq_report_by | Generate a stratified full DQ report | 
| 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 | 
| FLOAT | Data Types | 
| float | Data Types | 
| GOLDSTANDARD | Cross-item level metadata attribute name | 
| GRADING_RULESET | Well-known metadata column names, names of metadata columns | 
| GROUP_VAR_DEVICE | Well-known metadata column names, names of metadata columns | 
| GROUP_VAR_OBSERVER | Well-known metadata column names, names of metadata columns | 
| 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_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' | 
| 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 | 
| JUMP_LIST | Well-known metadata column names, names of metadata columns | 
| 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 | 
| 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 | 
| meta_data | Data frame with metadata about the study data on variable level | 
| meta_data_cross | Well known columns on the 'meta_data_cross-item' 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 | 
| MULTIVARIATE_OUTLIER_CHECK | Cross-item level metadata attribute name | 
| MULTIVARIATE_OUTLIER_CHECKTYPE | Cross-item level metadata attribute name | 
| nres | return the number of result slots in a report | 
| numeric | Data Types | 
| N_RULES | Cross-item and item level metadata attribute name | 
| OPTIONAL | Requirement levels of certain metadata columns | 
| 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 | 
| 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_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_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.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 | 
| 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 | 
| 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 | 
| 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) | 
| RULE | Cross-item level metadata attribute name | 
| SCALE_LEVEL | Well-known metadata column names, names of metadata columns | 
| SCALE_LEVELS | Scale Levels | 
| 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 | 
| TECHNICAL | Requirement levels of certain metadata columns | 
| TIME_VAR | Well-known metadata column names, names of metadata columns | 
| 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_SOURCES | Maturity stage of a unit according to 'units::valid_udunits()' | 
| UNIVARIATE_OUTLIER_CHECKTYPE | Item level metadata attribute name | 
| UNKNOWN | Requirement levels of certain metadata columns | 
| util_bar_plot | Utility function to create bar plots | 
| util_combine_list_report_summaries | Create a data frame containing all the results from summaries of reports | 
| util_compute_kurtosis | Compute Kurtosis | 
| util_compute_SE_skewness | Compute SE.Skewness | 
| util_compute_skewness | Compute the Skewness | 
| util_create_report_by_overview | Create an overview of the reports created with 'dq_report_by' | 
| util_first_row_to_colnames | Move the first row of a data frame to its column names | 
| util_get_encoding | Get encoding from metadata or guess it from data | 
| util_has_no_group_vars | Utility function to check whether a variable has no grouping variable assigned | 
| util_histogram | Utility function to create histograms | 
| util_margins_bin | Utility function to create a margins plot for binary variables | 
| util_margins_lm | Utility function to create a margins plot from linear regression models | 
| util_margins_nom | Utility function to create a plot similar to the margins plots for nominal variables | 
| util_margins_ord | Utility function to create a plot similar to the margins plots for ordinal variables | 
| util_margins_poi | Utility function to create a margins plot from Poisson regression models | 
| util_plot_categorical_vars | Utility function to create plots for categorical variables | 
| util_varcomp_robust | Utility function to compute the rank intraclass correlation | 
| 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_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 | 
| WELL_KNOWN_META_VARIABLE_NAMES | Well-known metadata column names, names of metadata columns | 
| $.dataquieR_resultset2 | Access single results from a dataquieR_resultset2 report | 
| $<-.dataquieR_resultset2 | Write single results from a dataquieR_resultset2 report | 
| .dataquieR_resultset2 | Class dataquieR_resultset2. | 
| [.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 |