| Get a subset of a 'dataquieR' 'dq_report2' report | [.dataquieR_resultset2 |
| Get a single result from a dataquieR 2 report | [[.dataquieR_resultset2 |
| Set a single result from a dataquieR 2 report | [[<-.dataquieR_resultset2 |
| Write to a report | [<-.dataquieR_resultset2 |
| Access single results from a dataquieR_resultset2 report | $.dataquieR_resultset2 cash-.dataquieR_resultset2 |
| Write single results from a dataquieR_resultset2 report | $<-.dataquieR_resultset2 cash-set-.dataquieR_resultset2.Rd |
| Plots and checks for distributions for categorical variables | acc_cat_distributions |
| Plots and checks for distributions | acc_distributions |
| ECDF plots for distribution checks | acc_distributions_ecdf |
| Plots and checks for distributions - Location | acc_distributions_loc |
| Plots and checks for distributions - only | acc_distributions_only |
| Plots and checks for distributions - Proportion | acc_distributions_prop |
| Extension of acc_shape_or_scale to examine uniform distributions of end digits | acc_end_digits |
| Smoothes and plots adjusted longitudinal measurements and longitudinal trends from logistic regression models | acc_loess |
| Estimate marginal means, see emmeans::emmeans | acc_margins |
| Calculate and plot Mahalanobis distances | acc_multivariate_outlier |
| Identify univariate outliers by four different approaches | acc_robust_univariate_outlier |
| Compare observed versus expected distributions | acc_shape_or_scale |
| Identify univariate outliers by four different approaches | acc_univariate_outlier |
| Utility function to compute model-based ICC depending on the (statistical) data type | acc_varcomp |
| Convert a full 'dataquieR' report to a 'data.frame' | as.data.frame.dataquieR_resultset |
| Convert a full 'dataquieR' report to a 'list' | as.list.dataquieR_resultset |
| inefficient way to convert a report to a list. try 'prep_set_backend()' | as.list.dataquieR_resultset2 |
| Cross-item level metadata attribute name | 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 | CHECK_ID |
| Cross-item level metadata attribute name | CHECK_LABEL |
| Data frame with contradiction rules | check_table |
| types of value codes | CODE_CLASSES |
| Default Name of the Table featuring Code Lists | CODE_LIST_TABLE |
| Only existence is checked, order not yet used | CODE_ORDER |
| Summarize missingness columnwise (in variable) | com_item_missingness |
| Compute Indicators for Qualified Item Missingness | com_qualified_item_missingness |
| Compute Indicators for Qualified Segment Missingness | com_qualified_segment_missingness |
| Summarizes missingness for individuals in specific segments | com_segment_missingness |
| Counts all individuals with no measurements at all | com_unit_missingness |
| Checks user-defined contradictions in study data | con_contradictions |
| Checks user-defined contradictions in study data | con_contradictions_redcap |
| Detects variable levels not specified in metadata | con_inadmissible_categorical |
| Detects variable levels not specified in standardized vocabulary | con_inadmissible_vocabulary |
| Detects variable values exceeding limits defined in metadata | con_limit_deviations |
| description of the contradiction functions | contradiction_functions_descriptions |
| Cross-item level metadata attribute name | CONTRADICTION_TERM RULE |
| Cross-item level metadata attribute name | CONTRADICTION_TYPE |
| Cross-item level metadata attribute name | DATA_PREPARATION |
| Data Types | DATA_TYPES DATETIME datetime enum FLOAT float INTEGER integer numeric set STRING string variable variable list |
| All available data types, mapped from their respective R types | DATA_TYPES_OF_R_TYPE |
| Internal constructor for the internal class dataquieR_resultset. | dataquieR_resultset |
| Verify an object of class dataquieR_resultset | dataquieR_resultset_verify |
| Class dataquieR_resultset2. | .dataquieR_resultset2 dataquieR_resultset2 dataquieR_resultset2-class |
| Exclude subgroups with constant values from LOESS figure | dataquieR.acc_loess.exclude_constant_subgroups |
| Display time-points in LOESS plots | dataquieR.acc_loess.mark_time_points |
| Lower limit for the LOESS bandwidth | dataquieR.acc_loess.min_bw |
| Lower limit for the proportion of cases or controls to create a smoothed time trend figure | dataquieR.acc_loess.min_proportion |
| default for Plot-Format in 'acc_loess()' | dataquieR.acc_loess.plot_format |
| Display observations in LOESS plots | dataquieR.acc_loess.plot_observations |
| Include number of observations for each level of the grouping variable in the 'margins' figure | dataquieR.acc_margins_num |
| Sort levels of the grouping variable in the 'margins' figures | dataquieR.acc_margins_sort |
| Apply min-max scaling in parallel coordinates figure to inspect multivariate outliers | dataquieR.acc_multivariate_outlier.scale |
| Color for empirical contradictions | dataquieR.col_con_con_empirical |
| Color for logical contradictions | dataquieR.col_con_con_logical |
| Log Level | dataquieR.CONDITIONS_LEVEL_TRHESHOLD |
| Add stack-trace in condition messages (to be deprecated) | dataquieR.CONDITIONS_WITH_STACKTRACE |
| Call 'browser()' on errors | dataquieR.debug |
| Removal of hard limits from data before calculating descriptive statistics. | dataquieR.des_summary_hard_lim_remove |
| Disable automatic post-processing of 'dataquieR' function results | dataquieR.dontwrapresults |
| Metadata describes more than the current study data | dataquieR.ELEMENT_MISSMATCH_CHECKTYPE |
| Set caller for error conditions (to be deprecated) | dataquieR.ERRORS_WITH_CALLER |
| Try to avoid fallback to string columns when reading files | dataquieR.fix_column_type_on_read |
| Flip-Mode to Use for figures | dataquieR.flip_mode |
| Converting MISSING_LIST/JUMP_LIST to a MISSING_LIST_TABLE create on list per item | dataquieR.force_item_specific_missing_codes |
| Control, how the 'label_col' argument is used. | dataquieR.force_label_col |
| Enable to switch to a general additive model instead of LOESS | dataquieR.GAM_for_LOESS |
| Name of the data.frame featuring a format for grading-values | dataquieR.grading_formats |
| Name of the data.frame featuring GRADING_RULESET | dataquieR.grading_rulesets |
| Control, if 'dataquieR' tries to guess missing-codes from the study data in absence of metadata | dataquieR.guess_missing_codes |
| Language-Suffix for metadata Label-Columns | dataquieR.lang |
| Maximum number of levels of the grouping variable shown individually in figures | dataquieR.max_group_var_levels_in_plot |
| Maximum number of levels of the grouping variable shown with individual histograms ('violins') in 'margins' figures | dataquieR.max_group_var_levels_with_violins |
| Maximum length for variable labels | dataquieR.MAX_LABEL_LEN |
| Maximum length for value labels | dataquieR.MAX_VALUE_LABEL_LEN |
| Set caller for message conditions (to be deprecated) | dataquieR.MESSAGES_WITH_CALLER |
| Minimum number of observations per grouping variable that is required to include an individual level of the grouping variable in a figure | dataquieR.min_obs_per_group_var_in_plot |
| Default availability of multivariate outlier checks in reports | dataquieR.MULTIVARIATE_OUTLIER_CHECK |
| Remove all observation-level-real-data from reports | dataquieR.non_disclosure |
| function to call on progress increase | dataquieR.progress_fkt |
| function to call on progress message update | dataquieR.progress_msg_fkt |
| Number of levels to consider a variable ordinal in absence of SCALE_LEVEL | dataquieR.scale_level_heuristics_control_binaryrecodelimit |
| Number of levels to consider a variable metric in absence of SCALE_LEVEL | dataquieR.scale_level_heuristics_control_metriclevels |
| Disable all interactively used metadata-based function argument provision | dataquieR.testdebug |
| Assume, all VALUE_LABELS are HTML escaped | dataquieR.VALUE_LABELS_htmlescaped |
| Set caller for warning conditions (to be deprecated) | dataquieR.WARNINGS_WITH_CALLER |
| Compute Pairwise Correlations | des_scatterplot_matrix |
| Compute Descriptive Statistics | des_summary |
| Compute Descriptive Statistics - categorical variables | des_summary_categorical |
| Compute Descriptive Statistics - continuous variables | des_summary_continuous |
| Data frame level metadata attribute name | 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 |
| Get the dimensions of a 'dq_report2' result | dim.dataquieR_resultset2 |
| Names of DQ dimensions | dimensions |
| Names of a 'dataquieR' report object (v2.0) | dimnames.dataquieR_resultset2 |
| Dimension Titles for Prefixes | dims |
| All available probability distributions for acc_shape_or_scale | DISTRIBUTIONS |
| Generate a full DQ report | dq_report |
| Generate a stratified full DQ report | dq_report_by |
| Generate a full DQ report, v2 | dq_report2 |
| Cross-item level metadata attribute name | GOLDSTANDARD |
| HTML Dependency for report headers in 'clipboard' | html_dependency_clipboard |
| HTML Dependency for 'dataquieR' | html_dependency_dataquieR |
| HTML Dependency for report headers in 'DT::datatable' | html_dependency_report_dt |
| HTML Dependency for 'tippy' | html_dependency_tippy |
| HTML Dependency for vertical headers in 'DT::datatable' | html_dependency_vert_dt |
| Wrapper function to check for studies data structure | int_all_datastructure_dataframe |
| Wrapper function to check for segment data structure | int_all_datastructure_segment |
| Check declared data types of metadata in study data | int_datatype_matrix |
| Check for duplicated content | int_duplicate_content |
| Check for duplicated IDs | int_duplicate_ids |
| Encoding Errors | int_encoding_errors |
| Detect Expected Observations | int_part_vars_structure |
| Determine missing and/or superfluous data elements | int_sts_element_dataframe |
| Checks for element set | int_sts_element_segment |
| Check for unexpected data element count | int_unexp_elements |
| Check for unexpected data record count at the data frame level | int_unexp_records_dataframe |
| Check for unexpected data record count within segments | int_unexp_records_segment |
| Check for unexpected data record set | int_unexp_records_set |
| Data frame with metadata about the study data on variable level | meta_data |
| Well known columns on the 'meta_data_cross-item' sheet | meta_data_cross |
| Well known columns on the 'meta_data_dataframe' sheet | meta_data_dataframe |
| Well known columns on the 'meta_data_segment' sheet | meta_data_segment |
| Cross-item level metadata attribute name | MULTIVARIATE_OUTLIER_CHECK |
| Cross-item level metadata attribute name | MULTIVARIATE_OUTLIER_CHECKTYPE |
| Cross-item and item level metadata attribute name | N_RULES |
| return the number of result slots in a report | nres |
| Convert a pipeline result data frame to named encapsulated lists | pipeline_recursive_result |
| Call (nearly) one "Accuracy" function with many parameterizations at once automatically | pipeline_vectorized |
| Plot a 'dataquieR' summary | plot.dataquieR_summary |
| Utility function to plot a combined figure for distribution checks | prep_acc_distributions_with_ecdf |
| Convert missing codes in metadata format v1.0 and a missing-cause-table to v2.0 missing list / jump list assignments | prep_add_cause_label_df |
| Insert missing codes for 'NA's based on rules | prep_add_computed_variables |
| Add data frames to the pre-loaded / cache data frame environment | prep_add_data_frames |
| Insert missing codes for 'NA's based on rules | prep_add_missing_codes |
| Support function to augment metadata during data quality reporting | prep_add_to_meta |
| Re-Code labels with their respective codes according to the 'meta_data' | prep_apply_coding |
| Check for package updates | prep_check_for_dataquieR_updates |
| Verify and normalize metadata on data frame level | prep_check_meta_data_dataframe |
| Verify and normalize metadata on segment level | prep_check_meta_data_segment |
| Checks the validity of metadata w.r.t. the provided column names | prep_check_meta_names |
| Support function to scan variable labels for applicability | prep_clean_labels |
| Combine two report summaries | prep_combine_report_summaries |
| Verify item-level metadata | prep_compare_meta_with_study |
| Support function to create data.frames of metadata | prep_create_meta |
| Instantiate a new metadata file | prep_create_meta_data_file |
| Create a factory function for 'storr' objects for backing a dataquieR_resultset2 | prep_create_storr_factory |
| Get data types from data | prep_datatype_from_data |
| Convert two vectors from a code-value-table to a key-value list | prep_deparse_assignments |
| Get the dataquieR 'DATA_TYPE' of 'x' | prep_dq_data_type_of |
| Expand code labels across variables | prep_expand_codes |
| Extract all missing/jump codes from metadata and export a cause-label-data-frame | prep_extract_cause_label_df |
| Extract old function based summary from data quality results | prep_extract_classes_by_functions |
| Extract summary from data quality results | prep_extract_summary |
| Extract report summary from reports | prep_extract_summary.dataquieR_result |
| Extract report summary from reports | prep_extract_summary.dataquieR_resultset2 |
| Read data from files/URLs | prep_get_data_frame |
| Fetch a label for a variable based on its purpose | prep_get_labels |
| Get data frame for a given segment | prep_get_study_data_segment |
| Return the logged-in User's Full Name | prep_get_user_name |
| Guess encoding of text or text files | prep_guess_encoding |
| Prepare a label as part of a link for 'RMD' files | prep_link_escape |
| List Loaded Data Frames | prep_list_dataframes |
| All valid voc: vocabularies | prep_list_voc |
| Pre-load a folder with named (usually more than) one table(s) | prep_load_folder_with_metadata |
| Load a 'dq_report2' | prep_load_report |
| Load a report from a back-end | prep_load_report_from_backend |
| Pre-load a file with named (usually more than) one table(s) | prep_load_workbook_like_file |
| Support function to allocate labels to variables | prep_map_labels |
| Merge a list of study data frames to one (sparse) study data frame | prep_merge_study_data |
| Convert item-level metadata from v1.0 to v2.0 | prep_meta_data_v1_to_item_level_meta_data |
| Support function to identify the levels of a process variable with minimum number of observations | prep_min_obs_level |
| Open a data frame in Excel | prep_open_in_excel |
| Support function for a parallel 'pmap' | prep_pmap |
| Prepare and verify study data with metadata | prep_prepare_dataframes |
| Clear data frame cache | prep_purge_data_frame_cache |
| Remove a specified element from the data frame cache | prep_remove_from_cache |
| Create a 'ggplot2' pie chart | prep_render_pie_chart_from_summaryclasses_ggplot2 |
| Create a 'plotly' pie chart | prep_render_pie_chart_from_summaryclasses_plotly |
| Guess the data type of a vector | prep_robust_guess_data_type |
| Save a 'dq_report2' | prep_save_report |
| Heuristics to amend a SCALE_LEVEL column and a UNIT column in the metadata | prep_scalelevel_from_data_and_metadata |
| Change the back-end of a report | prep_set_backend |
| Guess a metadata data frame from study data. | prep_study2meta |
| Classify metrics from a report summary table | prep_summary_to_classes |
| Prepare a label as part of a title text for 'RMD' files | prep_title_escape |
| Remove data disclosing details | prep_undisclose |
| Combine all missing and value lists to one big table | prep_unsplit_val_tabs |
| Get value labels from data | prep_valuelabels_from_data |
| Print a dataquieR result returned by dq_report2 | dataquieR_result print.dataquieR_result |
| Generate a RMarkdown-based report from a dataquieR report | print.dataquieR_resultset |
| Generate a HTML-based report from a dataquieR report | print.dataquieR_resultset2 |
| Print a 'dataquieR' summary | print.dataquieR_summary |
| Print a 'DataSlot' object | print.DataSlot |
| print implementation for the class 'interval' | print.interval |
| print a list of 'dataquieR_result' objects | print.list |
| Print a 'master_result' object | print.master_result |
| print implementation for the class 'ReportSummaryTable' | print.ReportSummaryTable |
| Print a 'Slot' object | print.Slot |
| Print a 'StudyDataSlot' object | print.StudyDataSlot |
| Print a 'TableSlot' object | print.TableSlot |
| Check applicability of DQ functions on study data | pro_applicability_matrix |
| Combine 'ReportSummaryTable' outputs | rbind.ReportSummaryTable |
| Cross-item level metadata attribute name | REL_VAL |
| Return names of result slots (e.g., 3rd dimension of dataquieR results) | resnames |
| Return names of result slots (e.g., 3rd dimension of dataquieR results) | resnames.dataquieR_resultset2 |
| Scale Levels | SCALE_LEVELS |
| Segment level metadata attribute name | SEGMENT_ID_REF_TABLE |
| Deprecated segment level metadata attribute name | SEGMENT_ID_TABLE |
| 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 |
| Character used by default as a separator in metadata such as missing codes | SPLIT_CHAR |
| Data frame with the study data whose quality is being assessed | study_data |
| Summarize a dataquieR report | summary.dataquieR_resultset |
| Generate a report summary table | summary.dataquieR_resultset2 |
| Is a unit a count according to 'units::valid_udunits()' | UNIT_IS_COUNT |
| Valid unit prefixes according to 'units::valid_udunits_prefixes()' | UNIT_PREFIXES |
| Maturity stage of a unit according to 'units::valid_udunits()' | UNIT_SOURCES |
| Valid unit symbols according to 'units::valid_udunits()' | UNITS |
| Item level metadata attribute name | UNIVARIATE_OUTLIER_CHECKTYPE |
| Utility function to create bar plots | util_bar_plot |
| Create a data frame containing all the results from summaries of reports | util_combine_list_report_summaries |
| Compute Kurtosis | util_compute_kurtosis |
| Compute SE.Skewness | util_compute_SE_skewness |
| Compute the Skewness | util_compute_skewness |
| Create an overview of the reports created with 'dq_report_by' | util_create_report_by_overview |
| Move the first row of a data frame to its column names | util_first_row_to_colnames |
| Get encoding from metadata or guess it from data | util_get_encoding |
| Utility function to check whether a variable has no grouping variable assigned | util_has_no_group_vars |
| Utility function to create histograms | util_histogram |
| Utility function to create a margins plot for binary variables | util_margins_bin |
| Utility function to create a margins plot from linear regression models | util_margins_lm |
| Utility function to create a plot similar to the margins plots for nominal variables | util_margins_nom |
| Utility function to create a plot similar to the margins plots for ordinal variables | util_margins_ord |
| Utility function to create a margins plot from Poisson regression models | util_margins_poi |
| Utility function to create plots for categorical variables | util_plot_categorical_vars |
| Utility function to compute the rank intraclass correlation | util_varcomp_robust |
| Data frame with labels for missing- and jump-codes #' Metadata about value and missing codes | cause_label_df CODE_CLASS CODE_INTERPRET CODE_LABEL CODE_VALUE missing_matchtable value/missing-lists value_label_table |
| Requirement levels of certain metadata columns | COMPATIBILITY OPTIONAL RECOMMENDED REQUIRED TECHNICAL UNKNOWN VARATT_REQUIRE_LEVELS |
| Cross-item level metadata attribute name | VARIABLE_LIST |
| Variable roles can be one of the following: | variable roles VARIABLE_ROLES |
| Well-known metadata column names, names of metadata columns | CONTRADICTIONS CO_VARS DATAFRAMES DATA_ENTRY_TYPE DATA_TYPE DECIMALS DETECTION_LIMITS DETECTION_LIMIT_LOW DETECTION_LIMIT_UP DISTRIBUTION ENCODING END_DIGIT_CHECK GRADING_RULESET GROUP_VAR_DEVICE GROUP_VAR_OBSERVER HARD_LIMITS HARD_LIMIT_LOW HARD_LIMIT_UP INCL_HARD_LIMIT_LOW INCL_HARD_LIMIT_UP INCL_LOCATION_LIMIT_LOW INCL_LOCATION_LIMIT_UP INCL_PROPORTION_LIMIT_LOW INCL_PROPORTION_LIMIT_UP INCL_SOFT_LIMIT_LOW INCL_SOFT_LIMIT_UP JUMP_LIST KEY_DATETIME KEY_DEVICE KEY_OBSERVER KEY_STUDY_SEGMENT LABEL LOCATION_LIMIT_LOW LOCATION_LIMIT_UP LOCATION_METRIC LOCATION_RANGE LONG_LABEL MISSING_LIST MISSING_LIST_TABLE PART_VAR PROPORTION_LIMIT_LOW PROPORTION_LIMIT_UP PROPORTION_RANGE RECODE_CASES RECODE_CONTROL SCALE_LEVEL SOFT_LIMITS SOFT_LIMIT_LOW SOFT_LIMIT_UP STANDARDIZED_VOCABULARY_TABLE STUDY_SEGMENT TIME_VAR UNIT VALUE_LABELS VALUE_LABEL_TABLE variable attribute VARIABLE_ORDER VARIABLE_ROLE VAR_NAMES WELL_KNOWN_META_VARIABLE_NAMES |
