dataquieR 2.5.1

• 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()

dataquieR 2.5.0

• 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

dataquieR 2.1.0

• 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

dataquieR 2.0.1

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

dataquieR 2.0.0

• 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

dataquieR 1.0.13

• fixed a left-over ~ from the ggplot2 updates causing acc_margins to fail for categorical variables

dataquieR 1.0.12

• 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.

dataquieR 1.0.11

• Addressed a problem with some test platforms
• Added funding agencies in the manual

dataquieR 1.0.10

• Fixed NEWS.md file
• Fixed documentation

dataquieR 1.0.9

• 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

dataquieR 1.0.8

• 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.

dataquieR 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.

dataquieR 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.

dataquieR 1.0.5

• 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

dataquieR 1.0.4

• 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.

dataquieR 1.0.3

• Addressed all comments by the CRAN reviewers, thank you.

dataquieR 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.

dataquieR 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.

dataquieR 1.0.0

• Initial CRAN release candidate