Running ‘testthat.R’ [225s/591s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > if (require("testthat")) {
  +   library(insight)
  + 
  +   is_dev_version <- length(strsplit(packageDescription("insight")$Version, "\\.")[[1]]) > 3
  + 
  +   if (is_dev_version) {
  +     Sys.setenv("RunAllinsightTests" = "yes")
  +   } else {
  +     Sys.setenv("RunAllinsightTests" = "no")
  +   }
  +   si <- Sys.info()
  + 
  +   osx <- tryCatch(
  +     {
  +       if (!is.null(si["sysname"])) {
  +         si["sysname"] == "Darwin" || grepl("^darwin", R.version$os)
  +       } else {
  +         FALSE
  +       }
  +     },
  +     error = function(e) {
  +       FALSE
  +     }
  +   )
  + 
  +   solaris <- tryCatch(
  +     {
  +       if (!is.null(si["sysname"])) {
  +         grepl("SunOS", si["sysname"], ignore.case = TRUE)
  +       } else {
  +         FALSE
  +       }
  +     },
  +     error = function(e) {
  +       FALSE
  +     }
  +   )
  + 
  +   # disable / enable if needed
  +   if (.Platform$OS.type == "unix" && is_dev_version) {
  +     Sys.setenv("RunAllinsightStanTests" = "yes")
  +   } else {
  +     Sys.setenv("RunAllinsightStanTests" = "no")
  +   }
  + 
  +   # if (!osx && !solaris) {
  +   #   test_check("insight")
  +   # }
  + 
  +   test_check("insight")
  + }
  Loading required package: testthat
  boundary (singular) fit: see help('isSingular')
  Some of the variables were in matrix-format - probably you used
    `scale()` on your data?
    If so, and you get an error, please try `datawizard::standardize()` to
    standardize your data.
  Confidence intervals are not yet supported for models of class 'mlm'.
  Confidence intervals are not yet supported for models of class
    'multinom'.
  Confidence intervals are not yet supported for models of class
    'multinom'.
  Confidence intervals are not yet supported for models of class
    'multinom'.
  Confidence intervals are not yet supported for models of class
    'multinom'.
  Confidence intervals are not yet supported for models of class
    'multinom'.
  Confidence intervals are not yet supported for models of class
    'multinom'.
  Confidence intervals are not yet supported for models of class
    'multinom'.
  Confidence intervals are not yet supported for models of class
    'multinom'.
  
  Re-fitting to get Hessian
  
  
  Re-fitting to get Hessian
  
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  [ FAIL 1 | WARN 14 | SKIP 16 | PASS 2421 ]
  
  ══ Skipped tests ═══════════════════════════════════════════════════════════════
  • On CRAN (6)
  • isFALSE(run_stan) is TRUE (5)
  • works interactively (5)
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error (test-mlogit.R:140:3): mblogit and mclogit is not linear ──────────────
  Error in `mclogit(factor(gear) ~ mpg + hp, data = mtcars, trace = FALSE)`: The response matrix has to be numeric.
  Backtrace:
      ▆
   1. └─mclogit::mclogit(factor(gear) ~ mpg + hp, data = mtcars, trace = FALSE) at test-mlogit.R:140:2
  
  [ FAIL 1 | WARN 14 | SKIP 16 | PASS 2421 ]
  Error: Test failures
  Execution halted