Running 'testthat.R' [95s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(psycho)
  > 
  > test_check("psycho")
  Failed with error:  'there is no package called 'GPArotation''
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 1).
  Rejecting initial value:
    Log probability evaluates to log(0), i.e. negative infinity.
    Stan can't start sampling from this initial value.
  Rejecting initial value:
    Log probability evaluates to log(0), i.e. negative infinity.
    Stan can't start sampling from this initial value.
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
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  ------------------------------------------------------------
  EXPERIMENTAL ALGORITHM:
    This procedure has not been thoroughly tested and may be unstable
    or buggy. The interface is subject to change.
  ------------------------------------------------------------
  
  
  
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  Success! Found best value [eta = 1] earlier than expected.
  
  Begin stochastic gradient ascent.
    iter       ELBO   delta_ELBO_mean   delta_ELBO_med   notes 
     100    -4e+002             1.000            1.000
     200    -2e+002             1.011            1.021
     300    -2e+002             0.682            1.000
     400    -2e+002             0.511            1.000
     500    -2e+002             0.409            0.024
     600    -2e+002             0.341            0.024
     700    -2e+002             0.293            0.002   MEDIAN ELBO CONVERGED
  
  Drawing a sample of size 1000 from the approximate posterior... 
  COMPLETED.
  ------------------------------------------------------------
  EXPERIMENTAL ALGORITHM:
    This procedure has not been thoroughly tested and may be unstable
    or buggy. The interface is subject to change.
  ------------------------------------------------------------
  
  
  
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  Success! Found best value [eta = 1] earlier than expected.
  
  Begin stochastic gradient ascent.
    iter       ELBO   delta_ELBO_mean   delta_ELBO_med   notes 
     100    -9e+004             1.000            1.000
     200    -6e+002            79.074          157.147
     300    -5e+002            52.759            1.000
     400    -2e+002            39.982            1.651
     500    -2e+002            31.989            1.000
     600    -2e+002            26.660            1.000
     700    -2e+002            22.854            0.130
     800    -2e+002            19.999            0.130
     900    -2e+002            17.778            0.018
    1000    -2e+002            16.000            0.018
    1100    -2e+002            15.902            0.016   MAY BE DIVERGING... INSPECT ELBO
    1200    -2e+002             0.188            0.014
    1300    -2e+002             0.176            0.014
    1400    -2e+002             0.011            0.014
    1500    -2e+002             0.010            0.013   MEAN ELBO CONVERGED
  
  Drawing a sample of size 1000 from the approximate posterior... 
  COMPLETED.
  Initial log joint probability = -100816
  Optimization terminated normally: 
    Convergence detected: relative gradient magnitude is below tolerance
  The Crawford-Howell (1998) t-test suggests no dissociation between test X and test Y (t(5) = 2.10, p = 0.09°). The patient's score on test X is not significantly altered compared to its score on test Y.
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
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  -- 1. Error: If it works. (@test-get_contrasts.stanreg.R#10)  ------------------
  number of items to replace is not a multiple of replacement length
  1: psycho::get_contrasts(fit, "Salary") at testthat/test-get_contrasts.stanreg.R:10
  2: get_contrasts.stanreg(fit, "Salary")
  3: fit %>% emmeans::emmeans(formula) %>% coda::as.mcmc() %>% as.matrix() %>% coda::as.mcmc() %>% 
         as.data.frame()
  4: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
  5: eval(quote(`_fseq`(`_lhs`)), env, env)
  6: eval(quote(`_fseq`(`_lhs`)), env, env)
  7: `_fseq`(`_lhs`)
  8: freduce(value, `_function_list`)
  9: function_list[[i]](value)
  10: as.matrix(.)
  11: as.matrix.mcmc(.)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 1).
  
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  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
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  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4).
  
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  1
  == testthat results  ===========================================================
  OK: 136 SKIPPED: 0 FAILED: 1
  1. Error: If it works. (@test-get_contrasts.stanreg.R#10) 
  
  Error: testthat unit tests failed
  Execution halted