R Under development (unstable) (2025-08-24 r88696 ucrt) -- "Unsuffered Consequences"
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> 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`
2025-08-25 21:26:22.871625: Finished reliability computation for trust_politics
2025-08-25 21:26:22.872211: Starting reliability computation for ethical_flexbility (variable 2 of 2).
2025-08-25 21:26:22.937149: 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.
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 0 | WARN 0 | SKIP 0 | PASS 391 ]
> 
> proc.time()
   user  system elapsed 
  23.78    0.98   24.76