CRAN Package Check Results for Package tidycomm

Last updated on 2026-09-03 21:53:39 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.4.2 7.45 153.12 160.57 OK
r-devel-linux-x86_64-debian-gcc 0.4.2 5.29 105.91 111.20 OK
r-devel-linux-x86_64-fedora-clang 0.4.2 108.13 OK
r-devel-linux-x86_64-fedora-gcc 0.4.2 118.04 OK
r-devel-windows-x86_64 0.4.2 10.00 164.00 174.00 ERROR
r-patched-linux-x86_64 0.4.2 7.77 144.40 152.17 OK
r-release-linux-x86_64 0.4.2 6.48 144.81 151.29 OK
r-release-macos-arm64 0.4.2 2.00 40.00 42.00 OK
r-release-macos-x86_64 0.4.2 5.00 160.00 165.00 OK
r-release-windows-x86_64 0.4.2 11.00 169.00 180.00 OK
r-oldrel-macos-arm64 0.4.2 OK
r-oldrel-macos-x86_64 0.4.2 5.00 207.00 212.00 OK
r-oldrel-windows-x86_64 0.4.2 14.00 212.00 226.00 OK

Check Details

Version: 0.4.2
Check: tests
Result: ERROR Running 'testthat.R' [34s] Running the tests in 'tests/testthat.R' failed. Complete output: > library(testthat) > library(tidycomm) Attaching package: 'tidycomm' The following object is masked from 'package:testthat': describe > > test_check("tidycomm") The Spearman correlation may involve tied values (they have the same rank), making it impossible to calculate an exact p-value and dfs. We suggest using Kendall's tau rank correlation, which is tailored to handle tied data. When using Kendall's tau correlation, the df is not applicable. Kendall's tau is based on concordant and discordant pairs of data, rather than on a mathematical distribution that would require the calculation of df. Adding missing grouping variables: `employment` Adding missing grouping variables: `employment` Adding missing grouping variables: `employment` Adding missing grouping variables: `employment` 2026-09-02 02:22:06.317731: Finished reliability computation for trust_politics 2026-09-02 02:22:06.319262: Starting reliability computation for ethical_flexbility (variable 2 of 2). 2026-09-02 02:22:06.449158: Finished reliability computation for ethical_flexbility The following unassigned values were found in country : Austria, Denmark, UK . They were recoded to the 'other' value ( 3 ). The following unassigned values were found in c : cde . They were recoded to the 'other' value ( NA ). When using Kendall's tau correlation, the df is not applicable. Kendall's tau is based on concordant and discordant pairs of data, rather than on a mathematical distribution that would require the calculation of df. When using Kendall's tau correlation, the df is not applicable. Kendall's tau is based on concordant and discordant pairs of data, rather than on a mathematical distribution that would require the calculation of df. The significant result from Levene's test suggests unequal variances among the groups, violating standard t-test assumptions. This necessitates the use of Welch approximation to the degrees of freedom, which is robust against heteroscedasticity. The significant result from Levene's test suggests unequal variances among the groups, violating standard t-test assumptions. This necessitates the use of Welch approximation to the degrees of freedom, which is robust against heteroscedasticity. The significant result from Levene's test suggests unequal variances among the groups, violating standard t-test assumptions. This necessitates the use of Welch approximation to the degrees of freedom, which is robust against heteroscedasticity. The significant result from Levene's test suggests unequal variances among the groups, violating standard ANOVA assumptions. This necessitates the use of Welch's ANOVA, which is robust against heteroscedasticity. The significant result from Levene's test suggests unequal variances among the groups, violating standard ANOVA assumptions. This necessitates the use of Welch's ANOVA, which is robust against heteroscedasticity. The significant result from Levene's test suggests unequal variances among the groups, violating standard t-test assumptions. This necessitates the use of Welch approximation to the degrees of freedom, which is robust against heteroscedasticity. Saving _problems/test-tdcmm_visualize-40.R The significant result from Levene's test suggests unequal variances among the groups, violating standard t-test assumptions. This necessitates the use of Welch approximation to the degrees of freedom, which is robust against heteroscedasticity. The significant result from Levene's test suggests unequal variances among the groups, violating standard ANOVA assumptions. This necessitates the use of Welch's ANOVA, which is robust against heteroscedasticity. [ FAIL 1 | WARN 0 | SKIP 0 | PASS 378 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test-tdcmm_visualize.R:39:3'): implemented visualize() calls return ggplot2 (gg) ── Error: object 'ggcoef_multinom' is not exported by 'namespace:ggstats' Backtrace: ▆ 1. ├─testthat::expect_s3_class(...) at test-tdcmm_visualize.R:39:3 2. │ └─testthat::quasi_label(enquo(object)) 3. │ └─rlang::eval_bare(expr, quo_get_env(quo)) 4. ├─tidycomm::visualize(correlate(WoJ, ethics_1, ethics_2, ethics_3)) 5. ├─tidycomm:::visualize.tdcmm_crrltn(...) 6. │ └─tidycomm:::visualize_correlate(x, which, .design) 7. │ ├─tidycomm::visualize(to_correlation_matrix(x), .design = design) 8. │ └─tidycomm:::visualize.tdcmm_crrltn(to_correlation_matrix(x), .design = design) 9. │ └─tidycomm:::visualize_to_correlation_matrix(x, .design) 10. │ └─... %>% ... 11. └─base::loadNamespace(x) 12. └─base::namespaceImportFrom(...) 13. └─base::importIntoEnv(impenv, impnames, ns, impvars) [ FAIL 1 | WARN 0 | SKIP 0 | PASS 378 ] Error: ! Test failures. Execution halted Flavor: r-devel-windows-x86_64

Version: 0.4.2
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: --- re-building 'v01_univariate.Rmd' using rmarkdown --- finished re-building 'v01_univariate.Rmd' --- re-building 'v02_bivariate.Rmd' using rmarkdown Quitting from v02_bivariate.Rmd:214-218 [unnamed-chunk-24] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <error/rlang_error> Error: ! object 'ggcoef_multinom' is not exported by 'namespace:ggstats' --- Backtrace: ▆ 1. ├─... %>% visualize() 2. ├─tidycomm::visualize(.) 3. ├─tidycomm:::visualize.tdcmm_crrltn(.) 4. │ └─tidycomm:::visualize_correlate(x, which, .design) 5. │ ├─tidycomm::visualize(to_correlation_matrix(x), .design = design) 6. │ └─tidycomm:::visualize.tdcmm_crrltn(to_correlation_matrix(x), .design = design) 7. │ └─tidycomm:::visualize_to_correlation_matrix(x, .design) 8. │ └─... %>% ... 9. └─base::loadNamespace(x) 10. └─base::namespaceImportFrom(...) 11. └─base::importIntoEnv(impenv, impnames, ns, impvars) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Error: processing vignette 'v02_bivariate.Rmd' failed with diagnostics: object 'ggcoef_multinom' is not exported by 'namespace:ggstats' --- failed re-building 'v02_bivariate.Rmd' --- re-building 'v03_reliability.Rmd' using rmarkdown --- finished re-building 'v03_reliability.Rmd' --- re-building 'v04_icr.Rmd' using rmarkdown --- finished re-building 'v04_icr.Rmd' --- re-building 'v05_scales.Rmd' using rmarkdown --- finished re-building 'v05_scales.Rmd' SUMMARY: processing the following file failed: 'v02_bivariate.Rmd' Error: Vignette re-building failed. Execution halted Flavor: r-devel-windows-x86_64