Running ‘testthat.R’ [124s/143s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(SimplyAgree)
  > 
  > test_check("SimplyAgree")
  Saving _problems/test-agree_nest-26.R
  Limit of Agreement = 95%
  Binomial proportions test and quantile regression for LoA
  
               agreement lower.ci upper.ci
  % within 2.5    0.9444   0.6935   0.9922
  Hypothesis Test: don't reject h0
  
  ###- Quantile Limits of Agreement (LoA) -###
            Estimate Lower CI Upper CI CI Level
  Lower LoA    -1.12  -1.4705  -0.7695     0.90
  Bias          0.04  -0.5362   0.6162     0.95
  Upper LoA     2.97   2.1954   3.7446     0.90
  
  Limit of Agreement = 95%
  Binomial proportions test and quantile regression for LoA
  
               agreement lower.ci upper.ci
  % within 2.5    0.9444   0.6935   0.9922
  Hypothesis Test: don't reject h0
  
  ###- Quantile Limits of Agreement (LoA) -###
                   Estimate Lower CI Upper CI CI Level
  Lower LoA @ 3.9  -1.52603  -1.9506 -1.10148     0.90
  Lower LoA @ 5.24 -0.58334  -0.7497 -0.41701     0.90
  Lower LoA @ 7.4   0.93837   0.6407  1.23608     0.90
  Bias @ 3.9       -0.73052  -1.3830 -0.07808     0.95
  Bias @ 5.24      -0.07238  -0.8096  0.66486     0.95
  Bias @ 7.4        0.99000  -0.9752  2.95519     0.95
  Upper LoA @ 3.9   0.52353  -1.9981  3.04516     0.90
  Upper LoA @ 5.24  2.27008   1.6152  2.92494     0.90
  Upper LoA @ 7.4   5.08940   1.8002  8.37859     0.90
  
  MOVER Limits of Agreement (LoA)
  95% LoA @ 2.5% Alpha-Level
  Data with Replicates
  
   Average of Both Methods    Bias            Bias CI Lower LoA Upper LoA
                     3.905 -0.3111   [-8.681, 8.0587]    -3.341     2.719
                     5.382  0.6522  [-3.8839, 5.1882]    -2.378     3.682
                     7.395  1.9651 [-7.7328, 11.6631]    -1.065     4.995
                LoA CI
   [-11.1274, 10.5051]
   [-10.1641, 11.4684]
    [-8.8511, 12.7814]
  
  SD of Differences = 1.546
  Bland-Altman Limits of Agreement (LoA) of the Ratio (x/y)
  95% LoA @ 2.5% Alpha-Level
  Log-transformed Data with Replicates
  
    Bias          Bias CI Lower LoA Upper LoA           LoA CI
   1.119 [0.6373, 1.9636]     0.639     1.958 [0.3961, 3.1593]
  
  Coefficient of Variation (%) = 33.0697
  MOVER Limits of Agreement (LoA) of the Ratio (x/y)
  95% LoA @ 2.5% Alpha-Level
  Log-transformed Data with Replicates
  
    Bias          Bias CI Lower LoA Upper LoA           LoA CI
   1.119 [0.6373, 1.9636]     0.639     1.958 [0.1511, 8.2835]
  
  Coefficient of Variation (%) = 33.0697
  MOVER Limits of Agreement (LoA)
  95% LoA @ 2.5% Alpha-Level
  Data with Replicates
  
     Bias         Bias CI Lower LoA Upper LoA            LoA CI
   0.7152 [-2.2296, 3.66]    -2.232     3.662 [-9.7686, 11.199]
  
  SD of Differences = 1.5036
  Limit of Agreement = 95%
  Replicate Data Points (true value does not vary)
  note: hypothesis test likely bogus with proportional bias.
  Hypothesis Test: don't reject h0
  
  ###- Bland-Altman Limits of Agreement (LoA) -###
            Estimate Lower CI Upper CI CI Level
  Bias        0.7046  -0.6846   2.0938     0.95
  Lower LoA  -2.2412  -9.7421  -0.4977     0.95
  Upper LoA   3.6504   1.9069  11.1513     0.95
  
  LoA at average of both measures. Please check plot.
  Limit of Agreement = 95%
  Replicate Data Points (true value does not vary)
  
  Hypothesis Test: No Hypothesis Test
  
  ###- Bland-Altman Limits of Agreement (LoA) -###
            Estimate Lower CI Upper CI CI Level
  Bias        0.7152  -0.6667   2.0971     0.95
  Lower LoA  -2.2317  -9.7686  -0.4779     0.95
  Upper LoA   3.6622   1.9084  11.1990     0.95
  
  Limit of Agreement = 95%
  Replicate Data Points (true value does not vary)
  
  Hypothesis Test: don't reject h0
  
  ###- Bland-Altman Limits of Agreement (LoA) -###
            Estimate Lower CI Upper CI CI Level
  Bias        0.7152  -0.6667   2.0971     0.95
  Lower LoA  -2.2317  -7.5482  -0.7295     0.90
  Upper LoA   3.6622   2.1599   8.9786     0.90
  
  Limit of Agreement = 80%
  Replicate Data Points (true value does not vary)
  
  Hypothesis Test: reject h0
  
  ###- Bland-Altman Limits of Agreement (LoA) -###
            Estimate Lower CI Upper CI CI Level
  Bias        0.7152 -0.09588   1.5263     0.75
  Lower LoA  -1.2117 -2.31316  -0.6769     0.50
  Upper LoA   2.6421  2.10732   3.7436     0.50
  
  Limit of Agreement = 80%
  Replicate Data Points (true value does not vary)
  
  Hypothesis Test: reject h0
  
  ###- Bland-Altman Limits of Agreement (LoA) -###
            Estimate Lower CI Upper CI CI Level
  Bias        0.7152 -0.09588   1.5263     0.75
  Lower LoA  -1.2117 -2.31316  -0.6769     0.50
  Upper LoA   2.6421  2.10732   3.7436     0.50
  
  [1] 79.0000000  0.8022956
  Weighted Deming Regression with 95% C.I. 
  
  Call:
  dem_reg(formula = y ~ x, data = df1, weighted = TRUE, error.ratio = 4, 
      conf.level = 0.95)
  
  Coefficients:
  (Intercept)           x 
      -0.3251      1.0309 
  
  Weighted Deming Regression with 95% C.I. 
  
  Call:
  dem_reg(formula = y ~ x + id, data = reps, id = "id", weighted = TRUE, 
      conf.level = 0.95)
  
  Coefficients:
  (Intercept)           x 
       3.4162      0.2808 
  
  Searching for N to achieve 70% power...
    Testing N = 30... CI: 99.0%, Joint: 100.0%
  
  Target power achieved!
  Searching for N to achieve 99% power...
    Testing N = 20... CI: 7.0%, Joint: 12.0%
    Testing N = 30... CI: 8.0%, Joint: 8.0%
  Searching for N to achieve 60% power...
    Testing N = 25... CI: 100.0%, Joint: 100.0%
  
  Target power achieved!
  Searching for N to achieve 60% power...
    Testing N = 25... CI: 100.0%, Joint: 100.0%
  
  Target power achieved!
  95% Limits of Agreement with Parametric Bootstrap 95% Confidence Intervals 
     Average Condition  Measures Estimate  Lower CI Upper CI
  1    36.67   23C/5.5      Bias   0.3206  0.179362  0.62307
  2    36.67   23C/5.5 Lower LoA  -0.1665 -0.524443  0.33045
  3    36.67   23C/5.5 Upper LoA   0.8078  0.581119  1.05272
  4    36.67   33C/5.5      Bias   0.2780  0.134837  0.42243
  5    36.67   33C/5.5 Lower LoA  -0.1214 -0.427868  0.11787
  6    36.67   33C/5.5 Upper LoA   0.6775  0.659564  0.85497
  7    36.67   33C/7.5      Bias   0.2812  0.044819  0.56938
  8    36.67   33C/7.5 Lower LoA  -0.1882 -0.255122  0.20856
  9    36.67   33C/7.5 Upper LoA   0.7505  0.312272  1.12957
  10   36.93   23C/5.5      Bias   0.2762  0.182737  0.47856
  11   36.93   23C/5.5 Lower LoA  -0.2109 -0.553161  0.18973
  12   36.93   23C/5.5 Upper LoA   0.7634  0.503896  0.99562
  13   36.93   33C/5.5      Bias   0.2336  0.133121  0.42297
  14   36.93   33C/5.5 Lower LoA  -0.1658 -0.420852  0.09898
  15   36.93   33C/5.5 Upper LoA   0.6331  0.546052  0.84975
  16   36.93   33C/7.5      Bias   0.2368  0.126981  0.47739
  17   36.93   33C/7.5 Lower LoA  -0.2326 -0.281824  0.12953
  18   36.93   33C/7.5 Upper LoA   0.7061  0.404113  1.00616
  19   37.29   23C/5.5      Bias   0.2147  0.045646  0.45151
  20   37.29   23C/5.5 Lower LoA  -0.2724 -0.592925  0.09455
  21   37.29   23C/5.5 Upper LoA   0.7019  0.338404  0.95560
  22   37.29   33C/5.5      Bias   0.1721  0.002820  0.53180
  23   37.29   33C/5.5 Lower LoA  -0.2273 -0.429871  0.11674
  24   37.29   33C/5.5 Upper LoA   0.5715  0.340632  0.96351
  25   37.29   33C/7.5      Bias   0.1752  0.004807  0.36982
  26   37.29   33C/7.5 Lower LoA  -0.2941 -0.450123  0.05227
  27   37.29   33C/7.5 Upper LoA   0.6446  0.428586  0.85544
  95% Limits of Agreement with Bootstrap 95% Confidence Intervals 
              estimate   lower.ci   upper.ci
  Mean Bias  0.2510000  0.1570124  0.3128609
  Lower LoA -0.1887407 -0.2883997 -0.1073991
  Upper LoA  0.6907407  0.5929600  0.8167491
  
  Coefficient of Variation (%):  19.1
  Standard Error of Measurement (SEM):  1.01
  Standard Error of the Estimate (SEE):  1.22
  Standard Error of Prediction (SEP):  1.9
  
  Intraclass Correlation Coefficients with  95 % C.I.
             Model         Measures  Type    ICC Lower CI Upper CI
  1 one-way random        Agreement  ICC1 0.1657 -0.09672   0.6434
  2 two-way random        Agreement  ICC2 0.2898  0.04290   0.6911
  3  two-way fixed      Consistency  ICC3 0.7148  0.41183   0.9258
  4 one-way random   Avg. Agreement ICC1k 0.4428 -0.54504   0.8783
  5 two-way random   Avg. Agreement ICC2k 0.6201  0.15204   0.8995
  6  two-way fixed Avg. Consistency ICC3k 0.9093  0.73690   0.9804
  
  
  Coefficient of Variation (%):  19.1
  Standard Error of Measurement (SEM):  1.01
  Standard Error of the Estimate (SEE):  1.22
  Standard Error of Prediction (SEP):  1.9
  
  Intraclass Correlation Coefficients with  95 % C.I.
             Model         Measures  Type    ICC Lower CI Upper CI
  1 one-way random        Agreement  ICC1 0.1657 -0.09672   0.6434
  2 two-way random        Agreement  ICC2 0.2898  0.04290   0.6911
  3  two-way fixed      Consistency  ICC3 0.7148  0.41184   0.9258
  4 one-way random   Avg. Agreement ICC1k 0.4428 -0.54504   0.8783
  5 two-way random   Avg. Agreement ICC2k 0.6201  0.15204   0.8995
  6  two-way fixed Avg. Consistency ICC3k 0.9093  0.73690   0.9804
  
  
  Coefficient of Variation (%): 19.1 95% C.I. [10.7, 25]
  Standard Error of Measurement (SEM): 1.01 95% C.I. [0.566, 1.32]
  Standard Error of the Estimate (SEE): 1.22 95% C.I. [0.65, 1.98]
  Standard Error of Prediction (SEP): 1.9 95% C.I. [0.967, 3.43]
  
  Intraclass Correlation Coefficients
             Model         Measures  Type    ICC Lower CI Upper CI
  1 one-way random        Agreement  ICC1 0.1657 -0.09672   0.6434
  2 two-way random        Agreement  ICC2 0.2898  0.04290   0.6911
  3  two-way fixed      Consistency  ICC3 0.7148  0.41184   0.9258
  4 one-way random   Avg. Agreement ICC1k 0.4428 -0.54504   0.8783
  5 two-way random   Avg. Agreement ICC2k 0.6201  0.15204   0.8995
  6  two-way fixed Avg. Consistency ICC3k 0.9093  0.73690   0.9804
  
  
  Coefficient of Variation (%):  19.1
  Standard Error of Measurement (SEM):  1.01
  Standard Error of the Estimate (SEE):  1.22
  Standard Error of Prediction (SEP):  1.9
  
  Intraclass Correlation Coefficients with  95 % C.I.
             Model         Measures  Type    ICC Lower CI Upper CI
  1 one-way random        Agreement  ICC1 0.1657 -0.09672   0.6434
  2 two-way random        Agreement  ICC2 0.2898  0.04290   0.6911
  3  two-way fixed      Consistency  ICC3 0.7148  0.41184   0.9258
  4 one-way random   Avg. Agreement ICC1k 0.4428 -0.54504   0.8783
  5 two-way random   Avg. Agreement ICC2k 0.6201  0.15204   0.8995
  6  two-way fixed Avg. Consistency ICC3k 0.9093  0.73690   0.9804
  
  Deming Regression with 95% C.I. 
  
  Call:
  dem_reg(formula = Y ~ X, data = ncss_deming1, error.ratio = 4, 
      weighted = FALSE, conf.level = 0.95)
  
  Coefficients:
  (Intercept)           X 
     -0.08974     1.00119 
  
  Deming Regression with 95% C.I. 
  
  Call:
  dem_reg(formula = Y ~ X, data = ncss_deming1, error.ratio = 4, 
      weighted = FALSE, conf.level = 0.95)
  
  Coefficients:
                coef      bias     se df lower.ci upper.ci        t p.value
  Intercept -0.08974 -0.044938 1.7220  8  -4.0607    3.881 -0.05212  0.9597
  Slope      1.00119  0.003529 0.1872  8   0.5696    1.433  0.00638  0.9951
  
  8 degrees of freedom
  Error variance ratio (lambda): 4.0000
  Passing-Bablok (scissors) with 95% C.I. 
  
  Call:
  pb_reg(formula = Method2 ~ Method1, data = ncss_pb1)
  
  Coefficients:
         term  coef       se lower.ci upper.ci df null_value reject_h0
  1 Intercept -0.15 0.377175  -0.8457   0.6328 28          0     FALSE
  2   Method1  1.00 0.006178   0.9880   1.0122 28          1     FALSE
  
  28 degrees of freedom
  Error variance ratio (lambda): 1.0000
  
  Deming Regression with 95% C.I. 
  
  Call:
  dem_reg(formula = Y ~ X, data = ncss_deming1, error.ratio = 4, 
      weighted = FALSE, conf.level = 0.95)
  
  Coefficients:
                coef      bias     se df lower.ci upper.ci        t p.value
  Intercept -0.08974 -0.044938 1.7220  8  -4.0607    3.881 -0.05212  0.9597
  Slope      1.00119  0.003529 0.1872  8   0.5696    1.433  0.00638  0.9951
  
  8 degrees of freedom
  Error variance ratio (lambda): 4.0000
  Agreement between Measures (Difference: x-y)
  95% Prediction Interval with 95% Tolerance Limits
  
     Bias          Bias CI Prediction Interval Tolerance Limits
   0.1908 [0.1462, 0.2355]   [-0.1578, 0.5395] [-0.2123, 0.594]
  
  
  Agreement between Measures (Difference: x-y)
  95% Prediction Interval with 95% Tolerance Limits
  
   Average of Both Methods   Bias          Bias CI Prediction Interval
                     36.38 0.2333 [0.1319, 0.3347]   [-0.1275, 0.5941]
                     36.83 0.1901 [0.1453, 0.2348]   [-0.1591, 0.5392]
                     37.23 0.1512 [0.0552, 0.2472]   [-0.2081, 0.5105]
    Tolerance Limits
    [-0.1844, 0.651]
   [-0.2141, 0.5943]
   [-0.2648, 0.5672]
  
  
  Agreement between Measures (Difference: x-y)
  95% Prediction Interval with 95% Tolerance Limits
  
     Bias          Bias CI Prediction Interval Tolerance Limits
   0.1908 [0.1191, 0.2625]   [-0.2098, 0.5915] [-0.3803, 0.762]
  
  
  Agreement between Measures (Difference: x-y)
  95% Prediction Interval with 95% Tolerance Limits
  
     Bias         Bias CI Prediction Interval Tolerance Limits
   0.1907 [0.1284, 0.253]   [-0.1828, 0.5642]  [-0.2986, 0.68]
  
  
  Agreement between Measures (Difference: x-y)
  95% Prediction Interval with 95% Tolerance Limits
  
     Bias         Bias CI Prediction Interval  Tolerance Limits
   0.1907 [0.1284, 0.253]   [-0.1828, 0.5642] [-0.2986, 0.6801]
  
  
  Agreement between Measures (Difference: x-y)
  95% Prediction Interval with 95% Tolerance Limits
  
   Condition   Bias          Bias CI Prediction Interval  Tolerance Limits
          AM 0.1581 [0.0786, 0.2377]   [-0.2164, 0.5327] [-0.3403, 0.6565]
          PM 0.2233 [0.1438, 0.3028]   [-0.1513, 0.5979] [-0.2751, 0.7217]
  
  
  Agreement between Measures (Difference: x-y)
  95% Prediction Interval with 95% Tolerance Limits
  
   Condition   Bias          Bias CI Prediction Interval  Tolerance Limits
          AM 0.1537 [0.0595, 0.2478]   [-0.2919, 0.5993]  [-0.3513, 0.642]
          PM 0.2280 [0.1342, 0.3218]   [-0.3162, 0.7722] [-0.3557, 0.8522]
  
  
  Agreement between Measures (Ratio: x/y)
  95% Prediction Interval with 95% Tolerance Limits
  
   Average of Both Methods  Bias          Bias CI Prediction Interval
                     36.38 1.005 [1.0014, 1.0082]    [0.9943, 1.0153]
                     36.83 1.005  [1.003, 1.0074]    [0.9935, 1.0171]
                     37.23 1.006 [1.0024, 1.0089]    [0.9952, 1.0161]
   Tolerance Limits
   [0.9921, 1.0176]
   [0.9877, 1.0231]
   [0.9928, 1.0185]
  
  
  Sympercent Difference between Methods (s%)
  95% Prediction Interval with 95% Tolerance Limits
  
   Average of Both Methods   Bias          Bias CI Prediction Interval
                     36.38 0.4745 [0.1362, 0.8128]   [-0.5679, 1.5169]
                     36.83 0.5194 [0.3011, 0.7377]    [-0.654, 1.6928]
                     37.23 0.5598 [0.2359, 0.8837]   [-0.4811, 1.6007]
    Tolerance Limits
   [-0.7957, 1.7447]
   [-1.2419, 2.2807]
   [-0.7182, 1.8378]
  
  
  Agreement between Measures (Ratio: x/y)
  95% Prediction Interval with 95% Tolerance Limits
  
   Condition Average of Both Methods  Bias          Bias CI Prediction Interval
          AM                   36.38 1.007 [1.0035, 1.0096]    [0.9955, 1.0176]
          PM                   36.38 1.010 [1.0062, 1.0139]    [0.9989, 1.0213]
          AM                   36.83 1.003  [1.001, 1.0057]     [0.992, 1.0149]
          PM                   36.83 1.007 [1.0047, 1.0091]    [0.9927, 1.0213]
          AM                   37.23 1.001 [0.9967, 1.0045]    [0.9895, 1.0117]
          PM                   37.23 1.004 [1.0015, 1.0066]    [0.9929, 1.0153]
   Tolerance Limits
   [0.9931, 1.0201]
   [0.9969, 1.0234]
   [0.9882, 1.0188]
   [0.9836, 1.0308]
   [0.9876, 1.0137]
   [0.9897, 1.0186]
  
  
  Agreement between Measures (Ratio: x/y)
  95% Prediction Interval with 95% Tolerance Limits
  
   Condition Average of Both Methods  Bias          Bias CI Prediction Interval
          AM                   36.38 1.007 [1.0035, 1.0096]    [0.9955, 1.0176]
          PM                   36.38 1.010 [1.0062, 1.0139]    [0.9989, 1.0213]
          AM                   36.83 1.003  [1.001, 1.0057]     [0.992, 1.0149]
          PM                   36.83 1.007 [1.0047, 1.0091]    [0.9927, 1.0213]
          AM                   37.23 1.001 [0.9967, 1.0045]    [0.9895, 1.0117]
          PM                   37.23 1.004 [1.0015, 1.0066]    [0.9929, 1.0153]
   Tolerance Limits
   [0.9929, 1.0206]
   [0.9958, 1.0253]
   [0.9897, 1.0174]
   [0.9917, 1.0218]
   [0.9854, 1.0156]
    [0.9899, 1.018]
  
  
  Agreement between Measures (Ratio: x/y)
  95% Prediction Interval with 95% Tolerance Limits
  
   Average of Both Methods  Bias          Bias CI Prediction Interval
                     36.38 1.005 [1.0014, 1.0082]    [0.9943, 1.0153]
                     36.83 1.005  [1.003, 1.0074]    [0.9935, 1.0171]
                     37.23 1.006 [1.0024, 1.0089]    [0.9952, 1.0161]
   Tolerance Limits
   [0.9903, 1.0181]
   [0.9918, 1.0193]
     [0.9928, 1.02]
  
  
  Limit of Agreement = 95%
  
  ###- Shieh Results -###
  Exact 90% C.I.  [-2.6418, 3.5184]
  Hypothesis Test: don't reject h0
  
  ###- Bland-Altman Limits of Agreement (LoA) -###
            Estimate Lower CI Upper CI CI Level
  Bias        0.4383  -0.1669    1.044     0.95
  Lower LoA  -1.9470  -2.8162   -1.078     0.90
  Upper LoA   2.8237   1.9545    3.693     0.90
  
  ###- Concordance Correlation Coefficient (CCC) -###
  CCC: 0.4791, 95% C.I. [0.1276, 0.7237]
  [ FAIL 1 | WARN 2 | SKIP 6 | PASS 682 ]
  
  ══ Skipped tests (6) ═══════════════════════════════════════════════════════════
  • On CRAN (6): 'test-deming_power.R:300:3', 'test-deming_power.R:318:3',
    'test-deming_power.R:354:3', 'test-deming_power.R:375:3',
    'test-deming_power.R:411:3', 'test-deming_power.R:439:3'
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-agree_nest.R:22:3'): examples from Zou ─────────────────────────
  <vctrs_error_subscript_oob/vctrs_error_subscript/rlang_error/error/condition>
  Error in `select(., avg, bias, SE, df, lower.CL, upper.CL)`: Can't select columns that don't exist.
  ✖ Column `lower.CL` doesn't exist.
  Backtrace:
       ▆
    1. ├─SimplyAgree::agreement_limit(...) at test-agree_nest.R:22:3
    2. │ └─SimplyAgree:::calc_loa_nest(...)
    3. │   └─... %>% select(avg, bias, SE, df, lower.CL, upper.CL)
    4. ├─dplyr::select(., avg, bias, SE, df, lower.CL, upper.CL)
    5. ├─dplyr:::select.data.frame(., avg, bias, SE, df, lower.CL, upper.CL)
    6. │ └─tidyselect::eval_select(expr(c(...)), data = .data, error_call = error_call)
    7. │   └─tidyselect:::eval_select_impl(...)
    8. │     ├─tidyselect:::with_subscript_errors(...)
    9. │     │ └─base::withCallingHandlers(...)
   10. │     └─tidyselect:::vars_select_eval(...)
   11. │       └─tidyselect:::walk_data_tree(expr, data_mask, context_mask)
   12. │         └─tidyselect:::eval_c(expr, data_mask, context_mask)
   13. │           └─tidyselect:::reduce_sels(node, data_mask, context_mask, init = init)
   14. │             └─tidyselect:::walk_data_tree(new, data_mask, context_mask)
   15. │               └─tidyselect:::as_indices_sel_impl(...)
   16. │                 └─tidyselect:::as_indices_impl(...)
   17. │                   └─tidyselect:::chr_as_locations(x, vars, call = call, arg = arg)
   18. │                     └─vctrs::vec_as_location(...)
   19. └─vctrs (local) `<fn>`() at vctrs/R/subscript-loc.R:84:3
   20.   └─vctrs:::stop_subscript_oob(...)
   21.     └─vctrs:::stop_subscript(...) at vctrs/R/subscript-loc.R:503:3
   22.       └─rlang::abort(...) at vctrs/R/subscript.R:150:3
  
  [ FAIL 1 | WARN 2 | SKIP 6 | PASS 682 ]
  Error:
  ! Test failures.
  Execution halted