Running ‘testthat.R’ [600s/473s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(insight)
  > test_check("insight")
  Starting 2 test processes
  [ FAIL 27 | WARN 506 | SKIP 73 | PASS 3434 ]
  
  ══ Skipped tests (73) ══════════════════════════════════════════════════════════
  • On CRAN (65): 'test-GLMMadaptive.R:1:1', 'test-averaging.R:3:1',
    'test-bias_correction.R:1:1', 'test-brms.R:1:1', 'test-brms_aterms.R:1:1',
    'test-brms_gr_random_effects.R:1:1', 'test-brms_missing.R:1:1',
    'test-brms_von_mises.R:1:1', 'test-blmer.R:249:3',
    'test-clean_names.R:103:3', 'test-clean_parameters.R:2:3',
    'test-clean_parameters.R:35:3', 'test-clmm.R:165:3', 'test-cpglmm.R:145:3',
    'test-export_table.R:4:3', 'test-export_table.R:8:3',
    'test-export_table.R:106:3', 'test-export_table.R:133:3',
    'test-export_table.R:164:3', 'test-export_table.R:193:3',
    'test-export_table.R:205:3', 'test-export_table.R:233:3',
    'test-find_random.R:27:3', 'test-format_table.R:1:1',
    'test-format_table_ci.R:71:3', 'test-gam.R:1:1', 'test-find_smooth.R:31:3',
    'test-get_data.R:385:1', 'test-get_loglikelihood.R:93:3',
    'test-get_loglikelihood.R:158:3', 'test-get_predicted.R:2:1',
    'test-get_priors.R:3:3', 'test-get_varcov.R:40:3',
    'test-is_converged.R:28:1', 'test-glmmTMB.R:71:3', 'test-glmmTMB.R:755:3',
    'test-glmmTMB.R:787:3', 'test-lme.R:34:3', 'test-lme.R:210:3',
    'test-marginaleffects.R:1:1', 'test-mgcv.R:1:1', 'test-mipo.R:1:1',
    'test-mvrstanarm.R:1:1', 'test-panelr-asym.R:142:3', 'test-panelr.R:272:3',
    'test-phylolm.R:5:1', 'test-r2_nakagawa_bernoulli.R:1:1',
    'test-r2_nakagawa_beta.R:1:1', 'test-r2_nakagawa_binomial.R:1:1',
    'test-r2_nakagawa_gamma.R:1:1', 'test-r2_nakagawa_linear.R:1:1',
    'test-r2_nakagawa_negbin.R:1:1', 'test-r2_nakagawa_negbin_zi.R:1:1',
    'test-r2_nakagawa_ordered_beta.R:1:1', 'test-r2_nakagawa_poisson.R:1:1',
    'test-r2_nakagawa_poisson_zi.R:1:1',
    'test-r2_nakagawa_truncated_poisson.R:1:1', 'test-r2_nakagawa_tweedie.R:1:1',
    'test-rlmer.R:259:3', 'test-rqss.R:1:1', 'test-rstanarm.R:1:1',
    'test-spatial.R:1:1', 'test-svylme.R:1:1', 'test-vgam.R:1:1',
    'test-weightit.R:1:1'
  • On Linux (3): 'test-BayesFactorBF.R:1:1', 'test-MCMCglmm.R:1:1',
    'test-get_data.R:150:3'
  • Package `logistf` is loaded and breaks `mmrm::mmrm()` (1): 'test-mmrm.R:4:1'
  • TRUE is TRUE (1): 'test-fixest.R:2:1'
  • works interactively (2): 'test-coxph-panel.R:34:3', 'test-coxph.R:38:3'
  • {bigglm} is not installed (1): 'test-model_info.R:24:3'
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Failure ('test-get_loglikelihood.R:216:3'): get_loglikelihood - gamm4 ───────
  as.numeric(ll) (`actual`) not equal to -101.1107 (`expected`).
  
    `actual`:  -99.1
  `expected`: -101.1
  ── Failure ('test-get_variance.R:49:3'): get_variance-1 ────────────────────────
  v1$var.intercept (`actual`) not equal to c(Subject = 612.10016) (`expected`).
  
    `actual`: 593.3
  `expected`: 612.1
  ── Failure ('test-get_variance.R:53:3'): get_variance-1 ────────────────────────
  v1$var.slope (`actual`) not equal to c(Subject.Days = 35.07171) (`expected`).
  
    `actual`: 593.3
  `expected`:  35.1
  ── Failure ('test-get_variance.R:60:3'): get_variance-2 ────────────────────────
  v2$var.intercept (`actual`) not equal to c(Subject = 627.56905) (`expected`).
  
    `actual`: 593.3
  `expected`: 627.6
  ── Failure ('test-get_variance.R:64:3'): get_variance-2 ────────────────────────
  v2$var.slope (`actual`) not equal to c(Subject.Days = 35.85838) (`expected`).
  
    `actual`: 593.3
  `expected`:  35.9
  ── Failure ('test-get_variance.R:71:3'): get_variance-3 ────────────────────────
  v3$var.intercept (`actual`) not equal to c(subgrp.grp.1 = 0, Subject = 662.52047, grp.1 = 0) (`expected`).
  
  `actual` is NULL
  `expected` is a double vector (0, 662.52047, 0)
  ── Failure ('test-get_variance.R:79:3'): get_variance-3 ────────────────────────
  v3$var.slope (`actual`) not equal to c(Subject.Days = 34.25771, subgrp.grp.Days = 7.88485, grp.Days = 0) (`expected`).
  
  `actual` is NULL
  `expected` is a double vector (34.25771, 7.88485, 0)
  ── Failure ('test-get_variance.R:91:3'): get_variance-4 ────────────────────────
  v4$var.intercept (`actual`) not equal to c(Subject = 1378.17851) (`expected`).
  
    `actual`:  811.1
  `expected`: 1378.2
  ── Failure ('test-get_variance.R:99:3'): get_variance-5 ────────────────────────
  v5$var.intercept (`actual`) not equal to c(`subgrp:grp` = 38.76069, Subject = 1377.50569, grp = 3.32031) (`expected`).
  
    `actual`: 654.2  654.2 654.2
  `expected`:  38.8 1377.5   3.3
  ── Failure ('test-get_variance.R:112:3'): get_variance-6 ───────────────────────
  v6$var.intercept (`actual`) not equal to c(plate = 0.71691) (`expected`).
  
    `actual`: 0.13
  `expected`: 0.72
  ── Failure ('test-get_variance.R:113:3'): get_variance-6 ───────────────────────
  v6$var.random (`actual`) not equal to 0.71691 (`expected`).
  
    `actual`: 0.13
  `expected`: 0.72
  ── Failure ('test-get_variance.R:124:3'): get_variance-7 ───────────────────────
  `vmodel` (`actual`) not equal to list(...) (`expected`).
  
    `actual$var.random`: 593.3
  `expected$var.random`: 627.6
  
    `actual$var.residual`: 593.3
  `expected$var.residual`: 653.6
  
    `actual$var.distribution`: 593.3
  `expected$var.distribution`: 653.6
  
    `actual$var.intercept`: 593.3
  `expected$var.intercept`: 627.6
  
    `actual$var.slope`: 593.3
  `expected$var.slope`:  35.9
  ── Failure ('test-get_variance.R:144:3'): get_variance-8 ───────────────────────
  `vmodel` (`actual`) not equal to list(...) (`expected`).
  
    `actual$var.random`: 21856.9
  `expected$var.random`:  1502.2
  
    `actual$var.residual`: 766.9
  `expected$var.residual`: 842.0
  
    `actual$var.distribution`: 766.9
  `expected$var.distribution`: 842.0
  
    `actual$var.slope`: 766.9
  `expected$var.slope`:  52.7
  ── Failure ('test-get_variance.R:169:3'): get_variance-9 ───────────────────────
  `vmodel` (`actual`) not equal to list(...) (`expected`).
  
    `actual$var.random`: 1264.6
  `expected$var.random`: 1711.4
  
    `actual$var.residual`: 790.4
  `expected$var.residual`: 748.8
  
    `actual$var.distribution`: 790.4
  `expected$var.distribution`: 748.8
  
    `actual$var.intercept`: 790.4
  `expected$var.intercept`: 663.3
  
    `actual$var.slope`: 790.4  790.4
  `expected$var.slope`: 882.4 1415.7
  
  actual$cor.slope_intercept vs expected$cor.slope_intercept
                                           [,1]
  - actual$cor.slope_intercept[1, ]   0.0000000
  + expected$cor.slope_intercept[1, ] 0.3611731
  - actual$cor.slope_intercept[2, ]   0.0000000
  + expected$cor.slope_intercept[2, ] 0.3318785
  
    `actual$cor.slopes`: 0.00
  `expected$cor.slopes`: 0.85
  ── Failure ('test-get_variance.R:198:3'): get_variance-10 ──────────────────────
  `vmodel` (`actual`) not equal to list(...) (`expected`).
  
  `actual` is length 8
  `expected` is length 7
  
      names(actual)      | names(expected)       
  [1] "var.fixed"        | "var.fixed"        [1]
  [2] "var.random"       -                       
  [3] "var.residual"     | "var.residual"     [2]
  [4] "var.distribution" | "var.distribution" [3]
  [5] "var.dispersion"   | "var.dispersion"   [4]
  
  `actual$var.random` is a double vector (739.145250002286)
  `expected$var.random` is absent
  
      names(actual$var.slope) | names(expected$var.slope)    
  [1] "Subject.1.Days2(3,6]"  -                              
  [2] "Subject.1.Days2(6,10]" -                              
  [3] "Subject.Days2(-1,3]"   | "Subject.Days2(-1,3]"     [1]
  [4] "Subject.Days2(3,6]"    | "Subject.Days2(3,6]"      [2]
  [5] "Subject.Days2(6,10]"   | "Subject.Days2(6,10]"     [3]
  
      actual$var.slope | expected$var.slope    
  [1] 739.145250002286 - 0                  [1]
  [2] 739.145250002286 - 994.015865559888   [2]
  [3] 739.145250002286 - 1545.72576115283   [3]
  [4] 739.145250002286 -                       
  [5] 739.145250002286 -                       
  
      names(actual$cor.slopes)            | names(expected$cor.slopes)            
  [1] "Subject.1.Days2(-1,3]-Days2(3,6]"  -                                       
  [2] "Subject.1.Days2(-1,3]-Days2(6,10]" -                                       
  [3] "Subject.1.Days2(3,6]-Days2(6,10]"  | "Subject.1.Days2(3,6]-Days2(6,10]" [1]
  
    `actual$cor.slopes`:                 0 0 0
  `expected$cor.slopes`: 0.859480774219098    
  ── Failure ('test-get_variance.R:222:3'): get_variance-11 ──────────────────────
  `vmodel` (`actual`) not equal to list(...) (`expected`).
  
    `actual$var.random`:  589.0
  `expected$var.random`: 1446.1
  
    `actual$var.residual`: 981.6
  `expected$var.residual`: 748.8
  
    `actual$var.distribution`: 981.6
  `expected$var.distribution`: 748.8
  
    `actual$var.slope`: 981.6  981.6  981.6
  `expected$var.slope`: 663.3 2098.2 2722.2
  
    `actual$cor.slopes`: 0.00 0.00 0.00
  `expected$cor.slopes`: 0.80 0.73 0.92
  ── Failure ('test-get_variance.R:250:3'): get_variance-12 ──────────────────────
  `vmodel` (`actual`) not equal to list(...) (`expected`).
  
    `actual$var.random`:  589.0
  `expected$var.random`: 1446.1
  
    `actual$var.residual`: 981.6
  `expected$var.residual`: 748.8
  
    `actual$var.distribution`: 981.6
  `expected$var.distribution`: 748.8
  
    `actual$var.slope`: 981.6  981.6  981.6
  `expected$var.slope`: 663.3 2098.2 2722.2
  
    `actual$cor.slopes`: 0.00 0.00 0.00
  `expected$cor.slopes`: 0.80 0.73 0.92
  ── Failure ('test-get_variance.R:283:3'): get_variance-cat_random_slope ────────
  vc$cor.slopes (`actual`) not equal to c(...) (`expected`).
  
    `actual`: 0.0 0.0 0.0 0.0 0.0 0.0  0.0  0.0  0.0  0.0
  `expected`: 1.0 1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 -1.0 -1.0
  ── Failure ('test-get_variance.R:326:3'): random effects CIs, simple slope ─────
  `vc` (`actual`) not equal to list(...) (`expected`).
  
    `actual[[1]]`: 935.7
  `expected[[1]]`: 921.9
  
    `actual[[2]]`: 17808.7
  `expected[[2]]`:  1068.0
  
    `actual[[3]]`: 624.9
  `expected[[3]]`: 764.5
  
    `actual[[4]]`: 624.9
  `expected[[4]]`: 764.5
  
    `actual[[6]]`: 624.9 624.9
  `expected[[6]]`:  37.5  27.6
  
    `actual[[7]]`: 0.00
  `expected[[7]]`: 0.46
  ── Failure ('test-get_variance.R:353:3'): random effects CIs, poly slope ───────
  vc$cor.slopes (`actual`) not equal to c(`replicate.poly(temp, 2)1-poly(temp, 2)2` = 0.940016422944175) (`expected`).
  
    `actual`: 0.00
  `expected`: 0.94
  ── Failure ('test-is_converged.R:23:3'): is_converged ──────────────────────────
  is_converged(model) is not TRUE
  
  `actual`:   FALSE
  `expected`: TRUE 
  ── Failure ('test-lmer.R:60:3'): get_df ────────────────────────────────────────
  get_df(m1, type = "satterthwaite") (`actual`) not equal to c(`(Intercept)` = 16.99973, Days = 16.99998) (`expected`).
  
    `actual`: 18.1 115.7
  `expected`: 17.0  17.0
  ── Failure ('test-lmer.R:334:3'): get_variance ─────────────────────────────────
  get_variance(m1) (`actual`) not equal to list(...) (`expected`).
  
    `actual$var.random`: 17503.7
  `expected$var.random`:  1698.1
  
    `actual$var.slope`: 593.3
  `expected$var.slope`:  35.1
  ── Failure ('test-lmer.R:353:3'): get_variance ─────────────────────────────────
  get_variance_random(m1) (`actual`) not equal to c(var.random = 1698.084) (`expected`).
  
    `actual`: 17503.7
  `expected`:  1698.1
  ── Failure ('test-lmer.R:377:3'): get_variance ─────────────────────────────────
  get_variance_slope(m1) (`actual`) not equal to c(var.slope.Subject.Days = 35.07171) (`expected`).
  
    `actual`: 593.3
  `expected`:  35.1
  ── Failure ('test-lmer.R:388:3'): get_variance ─────────────────────────────────
  suppressWarnings(get_variance(m2)) (`actual`) not equal to list(...) (`expected`).
  
  `actual` is length 6
  `expected` is length 5
  
      names(actual)      | names(expected)       
  [1] "var.fixed"        | "var.fixed"        [1]
  [2] "var.random"       -                       
  [3] "var.residual"     | "var.residual"     [2]
  [4] "var.distribution" | "var.distribution" [3]
  [5] "var.dispersion"   | "var.dispersion"   [4]
  
  `actual$var.random` is a double vector (2058.53584626217)
  `expected$var.random` is absent
  
    `actual$var.residual`: 686.2
  `expected$var.residual`: 941.8
  
    `actual$var.distribution`: 686.2
  `expected$var.distribution`: 941.8
  
    `actual$var.intercept`: 686.2  686.2 686.2
  `expected$var.intercept`:   0.0 1357.4  24.4
  ── Failure ('test-lmer.R:558:3'): get_predicted_ci: warning when model matrix and varcovmat do not match ──
  head(data.frame(p)$Predicted) (`actual`) not equal to known$Predicted (`expected`).
  
    `actual`: 37.586 47.556 56.800 65.318 73.111 80.177
  `expected`: 37.534 47.957 58.789 70.029 81.677 93.735
  
  [ FAIL 27 | WARN 506 | SKIP 73 | PASS 3434 ]
  Error: Test failures
  Execution halted