Changes in version 2.8.15.9005 - Limit-deviation plots now remain available when missing-code removal leaves exactly one usable observation, preventing a sparse variable from turning a multi-variable check into an empty result. Changes in version 2.8.15.9004 - Descriptive-summary color regression coverage now remains compatible with minimal installed-package validation environments where optional typo detection or interactive table backends are unavailable. Changes in version 2.8.15.9003 - Namespace-qualified descriptor calls such as dataquieR::des_summary(study_data) now keep their namespace when a data frame is supplied as the first positional argument, so attaching the package with library(dataquieR) is no longer required. - Standalone descriptive-summary frequency tables now show background colors when all categories have the same frequency instead of falling back to white. Changes in version 2.8.15.9002 - Excel exports from item- and variable-group dashboards now embed the visible plot previews alongside their rows. Active filters, sorting, and visible columns continue to determine the exported table. Preview-aware Excel, PDF, and Copy exports also work when a report bundle is opened directly from the local file system. - PDF exports from item- and variable-group dashboards now embed the visible plot previews in readable rows kept together. Active filters, sorting, pagination, and visible columns continue to determine the exported table, while missing previews leave clean empty cells. PDF, Excel, CSV, and Copy exports also preserve nested frequency tables as readable text instead of an unsupported-content placeholder. Copy exports use rich HTML where supported, so dashboard previews remain images when pasted into compatible applications; plain-text targets receive useful image labels. - Item dashboards again show result-specific diagnostic plots stored in SummaryPlotList for every corresponding metric row after a regression, while keeping variable distributions in their separate column. - Dashboard print exports now wait for visible plot previews to finish rendering before opening the print dialog, preventing incomplete output, including for report bundles opened directly from the local file system. - DQ_OBS Sunburst charts now group multiple result slots for the same variable and indicator into one variable leaf. All result classes remain part of the aggregation, and clicking a grouped leaf offers the underlying results for selection while avoiding white gaps caused by duplicate Plotly IDs. - Variable leaves in stratified report-overview Sunbursts now show the variable name before their shortened stratum context, so long data-set prefixes no longer hide the informative part of the label. Changes in version 2.8.15.9001 - Lifecycle badges are now included in synchronized public sources and installed packages, so help pages display their lifecycle status reliably. - Report tables rendered with the legacy DT backend and vertical scrolling no longer create a second, moving header. Their existing header remains visible, while headers on other report tables still follow the page scroll. - Report coverage tooltips now keep their published DQ_OBS concept link readable in normal, visited, hover, and keyboard-focus states. Changes in version 2.8.15 (2026-09-22) - HTML report tables now keep numeric descriptive statistics aligned with their variables when some results are empty. - Summary pie charts now display percentages consistently with one decimal place in both ggplot2 and Plotly output. - HTML report tables now keep their column headers visible while scrolling and recalculate column widths after responsive resizing with both the DT and DT2 backends. Metadata tables again reveal and hide automatically generated variables even when the displayed label differs from the variable name. - Fixed automatic study-data discovery in dq_report_by() so dataframe-level metadata remain separate from study records. This restores dataframe-level integrity results and prevents study records from appearing on metadata report pages. Overview calls no longer claim that study_data was supplied when it was discovered from dataframe-level metadata, preserve the distinction between omitted and explicitly empty response-variable selections, and correctly filter item-computation metadata for selected response variables. Changes in version 2.8.14 - Reduced CRAN check time by selecting a small, existing smoke-test set; the full test suite remains unchanged for local and CI runs. Changes in version 2.8.13 - Started support for structured text data, including syntax checks for JSON, XML, and YAML and schema checks for JSON and XML. - The dq_report_by() overview now displays effective dimension and indicator-function filters supplied through ... in its recorded call. - Assessment-scope concept coverage now includes published DQ_OBS indicators without a static function-to-entity mapping as reference goals. Additional package-specific indicators remain visible, and the report links to the published DQ_OBS concept for context. Changes in version 2.8.11 Major new features - Added dq_questionnaire() as a direct SSI/questionnaire analysis entry point. SSI reports now provide dedicated scale and metric pages, linked summaries, grading overviews, and section navigation. - Integrated variable-group and scale results throughout HTML reports, including dedicated detail pages, summary tables, dashboards, and hierarchy charts. Contradictions are separated from other group checks in summary pies and can be viewed separately or together in the interactive hierarchy chart. - Redesigned assessment-scope reporting for item- and variable-group results. Reports distinguish possible, requested, computed, and classified assessments, use entity- and datatype-specific DQ_OBS denominators, and represent joint assessments such as shape and scale without duplicating result metrics. - Made dq_report_by() results printable as report bundles while keeping its existing interfaces compatible. Results written to an output directory remain lightweight and can be rendered again from their saved .dq2 files; dir and output_dir are accepted consistently by dq_report2(), dq_report_by(), and their print methods. - Added grading-ruleset assignments and render-time grading for cross-item, segment-, and dataframe-level results. Segment missingness uses segment-level rulesets with a deterministic fallback. Explicitly supplied legacy thresholds remain supported and take precedence for that call. - Extended cross-item metadata patterns with [ALL], segment and dataframe selectors, and [WHERE {}]. Individual contradiction rules can select their grading ruleset explicitly. - Added experimental dq_shiny_panel_*() helpers for embedding existing results or report directories in Shiny applications. Important changes and improvements - Interactive report tables now use DataTables 2 through DT2 by default. When both DT2 and DT are installed, the automatic backend selection prefers DT2; it falls back to DT when DT2 is unavailable. Sorting, filtering, hover information, column visibility, SearchBuilder, and exports remain available. - Added machine-readable counts and percentages for uncertain and specified-reason item missingness. - Without an explicit legacy threshold, segment-missingness results retain raw metrics and receive classes and colors from the effective grading rules only when rendered. Ineffective threshold and direction columns are no longer returned. - Continuous acc_loess() group curves now use non-robust LOWESS iterations (iter = 0), matching the binary path. This may change computed curves compared with earlier releases. Installation and compatibility - Reduced installation dependencies by moving MASS to Suggests and replacing its required shape/scale parameter estimation with base-R implementations. Changes in version 2.8.10 Major new features - Added the first cross-item repeated-measurement assessment through acc_repeated_measurements(), including configurable statistical settings, internal ICC computation, and linked settings in HTML reports. - Replaced the parallelMap dependency with an in-package backend based on base R's parallel package. Existing parallel and MPI clusters remain supported, as do the relevant legacy parallelMap.* options. Breaking and important compatibility changes - Raised the minimum supported R version to R 4.1.0. - Scheduler modes named BatchJobs or batchtools no longer dispatch to these packages and fall back to sequential execution. Scheduler-backed execution should use dq_report2(..., mode = "futures") with an appropriate future plan. - Standardized cross-item metadata on the meta_data_cross_item attribute while retaining meta_data_cross as a compatibility fallback. - Added the option dataquieR.min_group_var_levels as the package-wide default for the minimum number of observed grouping-variable levels used by variance-component and margins analyses. This threshold could previously be changed only through function arguments or specific_args; the usual defaults were 5 (and 4 in one ordinal-margins path). The new default is 2. Ordinal mixed models still require at least 3 levels and raise smaller values accordingly. - The preliminary exported constants REL_VAL and GOLDSTANDARD were replaced by REPEATED_MEASURES_METRIC and REPEATED_MEASURES_REFERENCE, respectively. Changes in version 2.8.9 (2026-05-11) - Try to avoid spurious CRAN winbuilder fails. Changes in version 2.8.8 - Removed the dependency on the archived MultinomialCI package. Confidence intervals used by acc_shape_or_scale() and acc_end_digits() are now computed internally. The method can be selected with the option dataquieR.acc_shape_or_scale_ci. - Started experimental support for response quality. - Added pattern expansion for variable groups and rule templates, including support for expanded cross-item and computed rules. - Improved the dq_report_by() overview and subgroup handling, including more informative error messages for invalid subgroup rules. - Improved report rendering, including DataTables header filters, Plotly context-menu hooks, thumbnail font sizes, LOESS plots and sunburst charts. - Changed the default colors used for data-quality classes in sunburst charts to avoid counterintuitive mixed colors. - Changed margin plots for binary outcomes: by default, the overall distribution and geom_count are no longer shown. This can be controlled with the new no_overall_in_bin and no_geom_count_in_bin arguments and options. - Fixed filtering of cross-item and computed rules to keep only rules relevant for the selected response variables. - Fixed robustness issues in statistical indicators, metadata-v2 handling, JavaScript output and missing-list table rendering. Changes in version 2.8.7 (2026-01-08) - Fixed a bug in generated JavaScript containing variable labels with quotes - Fixed a bug in rendering, if some of the variables from the study data that are not covered in the metadata Changes in version 2.8.6 - Fixed race-condition with JavaScript and css in output - Fix in build-pipeline not affecting end-users Changes in version 2.8.5 - Improved css in output - Smaller installed package size Changes in version 2.8.4 - Added regression test based on the bug fixed in version 2.8.3. - Fixed a bug preventing some internal links from working. Changes in version 2.8.3 - Fixed a bug causing reports to be incomplete. Changes in version 2.8.2 (2025-12-22) - disabled slow tests Changes in version 2.8.1 - small fixes Changes in version 2.8.0 - Improved memory performance - Improved parallel rendering - Reduced internal documentation size - Documentation typos fixed; documentation improved and streamlined - Several test improvements; more robust handling of suggested packages - Removed bundled jsPDF HTML dependency; visNetwork is now suggested instead (saves ~356 KB installed size) - Various bug fixes related to new S7 rendering - Improved handling of options() - dq_report_by() no longer errors if plotly is missing but disables plotly functionality gracefully - Improved metadata page rendering Major internal change (may imply breaking changes) - ggplot2 objects are now returned as lightweight promises (dq_lazy_ggplot) to avoid serializing large S7 objects - If required, materialize explicitly via prep_realize_ggplot(p) - This reduces RAM demands but may require adaptation in downstream plot processing - If necessary, memory usage caused by S7 compatibility can be reduced via options(dataquieR.lazy_plots_gg_compatibility = "FALSE"), which may require more frequent calls to prep_realize_ggplot() - If you use saved report objects created with older ggplot2 / patchwork versions, they may stop working. Either recompute them or temporarily downgrade: remotes::install_version("patchwork", version = "1.3.0") remotes::install_version("ggplot2", version = "3.5.2") This workaround is only intended for restoring compatibility with previously saved report objects. No guarantee is given and you use it at your own risk. For long-term use, we recommend recomputing the reports with current package versions. - Factors are no longer converted to integers; they are converted to character first (controlled via option dataquieR.old_factor_handling) Other noteworthy changes Indicators, analytics & semantics - Added complex limits for cross-item_level metadata (HARD_LIMITS, SOFT_LIMITS, DETECTION_LIMITS). If both complex and item-level limits exist, complex limits take precedence - Work in progress: new Scales menu - Removed indicator PCT_acc_ud_loc from acc_margins() and grading rulesets - Removed metric FLG_acc_ud_loc from acc_margins() Rendering, tables & plots - Improved des_summary(): - restructured and more robust - column "No. categories/Freq. table" split into "No. categories (incl. NAs)" and "Level_freq" - column "Variables" renamed "Variable_names" (previous content now in attribute plain_label) - Correlation plots no longer depend on GGally - Proper and consistent date/time parsing - Better control over visibility of unused heatmap levels - Improved thumbnail handling and table variable columns Performance, robustness & infrastructure - Parallel rendering now more stable - Reduced RAM demands - Improved JavaScript utilities for handling results - More robust rendering in general - Improved error detection for inadmissible values in group variables with VALUE_LABELS - Experimental prep_init_parallel_print() removed (no longer needed) Changes in version 2.5.1 (2025-03-05) - News - fixed a bug found by latest R-developer-version caused by parentheses in the wrong position in encapsulated function calls. this did not cause any harm, but was nevertheless a bug. - properly deprecated the argument threshold_value from acc_varcomp() - loess and margins plot slightly improved - Amendment to 2.5.0 news - deprecated (and accidentally removed already) the argument threshold_value from acc_varcomp() Changes in version 2.5.0 (2025-02-20) - New features - improved support for categorical variables, including: - time trends w/ and w/o grouping variable - observer/device effects - distribution plots - dq_report2() can store results on the disk instead of the RAM with the new argument storr_factory. This can be useful in reducing issues of memory consumption, but we suggest to use fast SSDs or NVMes - all indicator functions now create result objects with nice print functions (visible in the Data Viewer instead of the Console window). However, this also implies, that warnings, errors and messages are returned as part of the result object and are printed with that object. If you want to restore the original behavior, use the option options(dataquieR.dontwrapresults = TRUE). With options(dataquieR.testdebug = TRUE), you can switch off this behavior. - dataquieR can provision your function arguments from the metadata. In order to enable lapply and Vectorize(SIMPLIFY = FALSE) with indicator functions, the first argument is now always resp_vars for item level functions. dataquieR tries to guess if a function that features both resp_vars and study_data as its first arguments was called w/o resp_vars but only with study_data as its first unnamed argument. If that is the case, it sets resp_vars to the default for resp_vars (typically all variables). With options(dataquieR.testdebug = TRUE), you can switch off this behavior, if you need. - an improved version of dq_report_by, in which it is possible to specify: - how to split the data in parts (strata and/or variable groups) - strata and/or variable groups to include/exclude - how to filter observational units - a selection of variables to analyze (resp_vars) - a variable/s containing ID information for merging data frames (id_vars) - a new function int_encoding_errors checking invalid characters present in the text with respect to the expected character encoding / code page, e.g., a code place in the latin1 table is used but the encoding is utf8 resulting in damaged text output - a new dashboard in the General menu, in Item-level data quality dashboard, usable to customize data summaries - new selection buttons are now present in the report to select visible columns in the displayed tables (it also applied to the export buttons) - support for a sheet CODE_LIST_TABLE in the metadata, where it is possible to state both value label tables and missing list tables all in one table. - support for a sheet item_computation_level in the metadata, where it is possible to state variables to be computed from the provided study data. - Breaking changes - moved example data from the package to our website. If you are already using prep_get_data_frame("ship") or prep_get_data_frame("study_data") in your code to access example data, no change is needed. If you are still accessing example data using system.file() (e.g. using load(system.file("extdata", "study_data.RData", package = "dataquieR"))), you need to switch to prep_get_data_frame(), i.e.: load(system.file("extdata", "study_data.RData", package = "dataquieR")) would become study_data <- prep_get_data_frame("study_data") - changes in the output names: - renamed SummaryData in ResultData (functions: acc_shape_or_scale, acc_margins, com_segment_missingness) - removed column GRADING from SummaryData outputs. SummaryTable outputs still feature the column, since these are meant to be a machine readable interface - con_contradictions_redcap used to return a result named SummaryTable, while the documentation spoke about SummaryData. Alas, it should have been VariableGroupTable in both cases. If you relied on SummaryTable in the results of con_contradictions_redcap, you need to change your code to use now the correct output name VariableGroupTable. Also, the table has been slightly modified. - VariableGroupData as returned by con_contradictions_redcap is a version optimized for human readers. - in VariableGroupTable as returned by con_contradictions_redcap the column category has been renamed to CONTRADICTION_TYPE - in con_contradictions_redcap, if summarize_categories is selected the result will now be in a sub-list named Other - in prep_add_computed_variables, the column resp_vars is now named VAR_NAMES, to be more in line with other data frames. - Reporting - improved button to export Excel, pdf, and print (colors supported) - improved rendering time introducing thumbnails as first visible result in the report. Clicking on the image, the thumbnail is replaced by plotly's interactive figures - implementation of [.dataquieR_resultset2 and [[.dataquieR_result and related functions have changed slightly. You can now for a report (r <- dq_report2(...)) call, e.g., r[, "com_item_missingness", "ReportSummaryTable"] to get a balloon plot or r[, "com_item_missingness", "SummaryData"] to get a table, for all variables that were assessed with com_item_missingness() in the report r - if you print a list of dataquieR_result objects, these will be combined, but due to restrictions in R, this only works, if you call print() explicitly on this list, not with "auto-printing" (see https://stackoverflow.com/a/53983005), for example: a <- lapply(c("v00001", "v00004", "v00005", "v00006"), acc_loess, meta_data_v2 = "meta_data_v2", study_data = "study_data") print(a) works, but typing a alone does not. You have to call print() or to put lapply() in brackets: (lapply()) - (Indicator) Functions related - acc_distributions() was split in acc_distributions() and acc_distributions_ecdf() (prep_acc_distributions_with_ecdf() creates the original plot) - there is a new function acc_cat_distributions() - all functions now feature: - a meta_data_v2 argument - new argument item_level, as synonyms for meta_data, new argument segment_level, as synonyms for meta_data_segment, new argument dataframe_level, as synonyms for meta_data_dataframe, new argument cross-item_level, as synonyms for meta_data_cross_item, new argument item_computation_level, as synonyms for meta_data_item_computation - if you call functions without label_col, the label_col will now default to LABEL, except you set the option options(dataquieR.testdebug = TRUE) or options(dataquieR.dontwrapresults = TRUE) - the argument resp_vars in prep_scalelevel_from_data_and_metadata() was never working correctly and not used neither, so it has been deprecated. It is already not functional and it never was - the function des_summary is still present, but you can now get results for continuous or categorical variables only, using des_summary_continuous and des_summary_categoricalrespectively - con_contradictions_redcap plot colors vary depending on CONTRADICTION_TYPES - acc_loess() uses lowess instead of loess (both from the stats package) - General - test coverage increased, again - fixed bug in prep_check_for_dataquieR_updates(), so, maybe, you need to manually install the latest beta release using devtools::install_gitlab("libreumg/dataquieR", auth_token = NULL) - figure sizes have been overworked in the default report - options(dataquieR.ELEMENT_MISSMATCH_CHECKTYPE = "subset_u") is now the default assuming a one-fits-all-metadata-file (see ? dataquieR.ELEMENT_MISSMATCH_CHECKTYPE) - fewer custom implementations of stuff available from rlang or withr, most prominently a faster prep_prepare_dataframes() and rlang compatible condition (error) handling. - small changes in the behavior of the dataquieR_result class, which is now applied also to results outside a pipeline. - many small fixes to figures - small fixes to menu titles - bug fixes Changes in version 2.1.0 (2024-03-29) - renamed metadata column SEGMENT_ID_TABLE to SEGMENT_ID_REF_TABLE in segment level metadata - scale level metadata support and heuristics - significantly improved data quality summaries - consolidated some of the indicator functions (limits, work in progress) - many minor optimizing changes - figure sizing (work in progress), also resize handles - improved report files structure - improved dq_report_by files structure - fixes, e.g., in rules, fixes in label shortening, computation speed and cache pre-filling-control - improved Excel export from the HTML reports - missing codes: column CODE_INTERPRET changed to be in line with the AAPOR definitions, so the following translation: PP -> P; P -> I; OH -> UO - fixed tests - updated concept excerpt - excluded nominal and ordinal variables from marginal means analysis - improved data type handling Changes in version 2.0.1 (2023-07-19) Reporting - New functions prep_save_report and prep_load_report - Update and simplification of summary overview, empty columns/rows omitted from the matrices. Also, better classification of errors - Many small updates in the usability of the report - Fixes in HTML/JS output for Firefox - Bug fixes of report outputs that were not looking as expected (in contradiction checks and limit violations) - Fixed mixed distribution plots called several times - Enable auto-resizing of plot.ly-plots - Fixed rendering problems for the new, automatically size-reduced plots causing the report rendering to fail if having gginnards installed; removed dependency from gginnards. - Do not show superfluous axis labels (e.g., variables, if variable names are on an axis because these usually overlap without improving the output) - Prevent a warning of robustbase about doScale - Less noisy display of conditions (e.g., warnings, errors, messages) with the results in dq_report2 reports - summarytools are included in dq_report2 reports, if installed. - New report rendering code polished, parallel execution of HTML generation prepared - New parallel mode for dq_report2 using a queue improves speed - Full support for VARIABLE_ROLES in dq_report2 and suppressing helper variable outputs in dq_report_by - Do not show conditions (e.g., warnings, messages, errors) in reports if they address the call of the function (e.g., "using default for argument...") by dq_report2 and not directly by the user - No unit-missingness in dq_report2 because it is not so useful in its current implementation - More robust dq_report_by for large reports (can write and optionally render results to disk rather than returning them) - Bug fix in dq_report_by causing DATA_PROCESS not to work - Fixed some errors and TODO's in dq_report_by and add dependent variables on the fly but with VARIABLE_ROLE suppress: - If no role is given, add "primary" by default for single reports as well as for dq_report_by - Support meta_data_v2 in dq_report_by - FIXED: referred variables did not correctly resolve co_vars and labels instead of variable names - Several bug fixes: - Addressed most parts of https://gitlab.com/libreumg/dataquier/-/issues/242 - Addressed https://gitlab.com/libreumg/dataquier/-/issues/244 and https://gitlab.com/libreumg/dataquier/-/issues/212 - Default for result-slot-filter was not set (filter_result_slots in dq_report2) - Sometimes, long labels in the first columns of a JS-table prevented controlling the table (Indicator) Functions related - Fixed missed check for missing cross-item level metadata and earlier check for valid item-level metadata - Control crude segment missingness output, so that we see it only if there is more than one segment on the item-level after the removal of VARIABLE_ROLES filtered items - Outliers should work with empty metadata in UNIVARIATE_OUTLIER_CHECKTYPE and MULTIVARIATE_OUTLIER_CHECKTYPE - Fixed successive dates to ignore empty dates - New functions in REDCap syntax: strictly_successive_dates and successive_dates - Bug fixes for REDCap rules and NA handling and DATA_PROCESS. - Checked, that code is in line with https://gitlab.com/libreumg/dataquier/-/issues/243#note_1419465360 - Default for contradictions with the new syntax is now that hard limits and missing codes are not removed. The argument use_value_labels is not supported anymore. You can specify the behavior on the rules level in the new cross-item-level metadata column DATA_PREPARATION - Compute end digit preferences only if explicitly requested by a new item-level metadata column END_DIGIT_CHECK in dq_report2, (DATA_ENTRY_TYPE is still supported and auto-converted). If missing, END_DIGIT_CHECK defaults to FALSE - Bug fix: Contradiction rules failed in specific cases if NA were in the data - Bug fix: cross-item_level normalization crashed, causing rules to fail, e.g., JUMP_LIST could be added to the item-level metadata if missing, but causing this type of failing rules - Bug fixes for Windows and uncommon variable names General - Workbooks can now be loaded from the internet (using prep_load_workbook_like_file and meta_data_v2 = formal in dq_report2) supporting http and https URLs (e.g., Excel or OpenOffice workbooks) - Documentation updates Changes in version 2.0.0 (2023-03-01) - dq_report2 replaces dq_report. Please use dq_report2 from now on. - Full new reporting engine (needs htmtools and supports plotly) - Better report layout and improved functionality - Support for reading and referring to data in files/URLs - Support for the integrity dimension in data quality report - Included distribution and multivariate outlier (provide cross-item level metadata for the latter) plots in data quality report - Metadata scheme update (segment, data.frame, and cross-item levels). No required action by user, previous version still supported - REDCap rules for contradictions (cross-item level metadata), previous contradictions function still supported - Support metadata describing segment data and study data tables (segment and data.frame-level metadata) - New item-level metadata version (backwards compatible) - Support for computation of qualified missingness based on labels from the AAPOR concept - acc_univariate_outlier and acc_multivariate_outlier now allow selecting the methods used to flag outliers - Included distributional checks in the accuracy dimension for location and proportion - Rotation of plots can now be controlled - Improved many figures - Better control over warnings - If whoami is installed, reports now show a more suitable user name - Many minor improvements - Updated citations Changes in version 1.0.13 (2022-11-16) - fixed a left-over ~ from the ggplot2 updates causing acc_margins to fail for categorical variables Changes in version 1.0.12 (2022-11-11) - Addressed a problem with the markdown template underlying the dq_report reports with wrong brackets - Addressed deprecations from ggplot2 3.4.0 - Added ORCIDs for two authors - Updated the CITATION file - Updated the README.md file adding the funding sources. Changes in version 1.0.11 (2022-10-11) - Addressed a problem with some test platforms - Added funding agencies in the manual Changes in version 1.0.10 (2022-08-31) - Fixed NEWS.md file - Fixed documentation Changes in version 1.0.9 (2021-09-03) - Fixed bug in sigmagap and made missing guessing more robust. - Fixed checks on missing code detection failing for logical. - Fixed a damaged check for numeric threshold values in acc_margins. - Fixed wrongly named GRADING columns. - Improved parallel execution by automatic detection of cores. - Tidy html dependency Changes in version 1.0.8 (2021-08-12) - Removed formal arguments from rbind.ReportSummaryTable since these are not needed anyways and the inherited documentation for those arguments rbind from base contains an invalid URL triggering a NOTE. Changes in version 1.0.7 - Fixed bugs in example metadata. - Figures now have size hints as attributes. - Added simple type conversion check indicator function of dimension integrity, int_datatype_matrix. - Corrected some error classifications - prep_study2meta can now also convert factors to dataquieR compatible meta_data/study_data - Slightly improved documentation. - Bug fix in com_item_missingness for textual response variables. - Added new output slot with heat-map like tables. Implemented some generics for those. Changes in version 1.0.6 - Robustness: Ensure DT JS is always loaded when a dq_report report is rendered - Bug fix: More robust handling of DECIMALS variable attribute, if this is delivered as a character. - Bug Fix: com_segment_missingness with strata_vars / group_vars did not work - Bug Fix: If label_col was set to something else than LABEL, strata_vars did not work for com_unit_missingness - More precise documentation. - Fixed a bug in a utility function for the univariate outliers indicator function, which caused many data points flagged as outliers by the sigma- gap criterion. - Made outlier function aware of too many non-outlier points causing too complex graphics (e.g. pdf rendering crashes the PDF reader). - Fixes and small improvements in dq_report. - Switched from cowplot to patchwork in acc_margins yielding figures that can be easier manipulated. Please note, that this change could break existing output manipulations, since the structure of the margins plots has changed internally. However, output manipulations were hardly possible for margins plots before, so it is unlikely, that there are pipelines affected. - More control about the output of the acc_loess function. - More robust prep_create_meta handling length-0 arguments by ignoring these variable attributes at all. - Added a classification system for warnings and error messages to distinguish errors based on mismatching variables for a function from other error messages. - JOSS - Some tidy up and more tests. Changes in version 1.0.5 (2021-02-26) - Fixed two bugs in con_inadmissible_categorical (one resp_var only and value-limits all the same for all resp_vars) - Changed LICENSE to BSD-2 - Slightly updated documentation - Updated README-File Changes in version 1.0.4 (2021-02-02) - Fixed CITATION, a broken reference in Rd and a problem with the vignette on pandoc-less systems - Improved an inaccurate argument description for multivariate outliers - Fixed a problem with error messages, if a dataquieR function was called by a generated function f that lives in an environment directly inheriting from the empty environment, e.g. environment(f) <- new.env(parent = emptyenv()). - Marked some examples as dontrun, because they sometimes caused NOTEs on rhub. Changes in version 1.0.3 (2021-01-26) - Addressed all comments by the CRAN reviewers, thank you. Changes in version 1.0.2 - Bug Fix: If an empty data frame was delivered in the SummaryTable entry of a result within a dq_report output, the summary and also print generic did not work on the report. Changes in version 1.0.1 - Skipping some of the slower tests on CRAN now. On my local system, a full devtools::check(cran = TRUE, env_vars = c(NOT_CRAN = "false")) takes 2:22 minutes now. Changes in version 1.0.0 - Initial CRAN release candidate