R Under development (unstable) (2023-08-16 r84968 ucrt) -- "Unsuffered Consequences" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(IRTest) Thank you for using IRTest! Please cite the package as: Li, S. (2022). IRTest: Parameter estimation of item response theory with estimation of latent distribution (Version 1.7.0). R package. URL: https://CRAN.R-project.org/package=IRTest > > test_check("IRTest") Method = N, EM cycle = 1, Max-Change = 1.466598916666 Method = N, EM cycle = 2, Max-Change = 0.213146463826426 Method = N, EM cycle = 1, Max-Change = 1.466598916666 Method = N, EM cycle = 2, Max-Change = 0.213146463826426 Method = N, EM cycle = 1, Max-Change = 1.2843675838483 Method = N, EM cycle = 2, Max-Change = 0.18239830362118 Method = N, EM cycle = 1, Max-Change = 1.39426751485116 Method = N, EM cycle = 2, Max-Change = 0.256406532967279 Method = EHM, EM cycle = 1, Max-Change = 1.466598916666 Method = EHM, EM cycle = 2, Max-Change = 0.211900842370132 Method = 2NM, EM cycle = 1, Max-Change = 1.47410887396381 Method = 2NM, EM cycle = 2, Max-Change = 0.209629532647032 Method = KDE, EM cycle = 1, Max-Change = 1.466598916666 Method = KDE, EM cycle = 2, Max-Change = 0.203519741464386 Method = DC, EM cycle = 1, Max-Change = 1.44010676263669 Method = DC, EM cycle = 2, Max-Change = 0.201151662692394 Method = LLS, EM cycle = 1, Max-Change = 1.46659691542266 Method = LLS, EM cycle = 2, Max-Change = 0.213849868544924 Method = 2NM, EM cycle = 1, Max-Change = 0 Method = N, EM cycle = 1, Max-Change = 6.38061382384528 Method = N, EM cycle = 2, Max-Change = 1.95531367162699 Method = EHM, EM cycle = 1, Max-Change = 6.38061382384528 Method = EHM, EM cycle = 2, Max-Change = 2.11582132494035 Method = 2NM, EM cycle = 1, Max-Change = 6.38061382384528 Method = 2NM, EM cycle = 2, Max-Change = 1.95531367162699 Method = KDE, EM cycle = 1, Max-Change = 6.38061382384528 Method = KDE, EM cycle = 2, Max-Change = 1.96696546884408 Method = DC, EM cycle = 1, Max-Change = 6.20432507945272 Method = DC, EM cycle = 2, Max-Change = 1.80234350013234 Method = LLS, EM cycle = 1, Max-Change = 6.38061362465624 Method = LLS, EM cycle = 2, Max-Change = 1.96521212930073 Method = N, EM cycle = 1, Max-Change = 2.55558861299848 Method = N, EM cycle = 2, Max-Change = 0.412696472571701 Method = N, EM cycle = 1, Max-Change = 6.09021485674526 Method = N, EM cycle = 2, Max-Change = 3.33203794139169 Method = EHM, EM cycle = 1, Max-Change = 6.09021485674526 Method = EHM, EM cycle = 2, Max-Change = 3.73964511542601 Method = 2NM, EM cycle = 1, Max-Change = 2.87047514297627 Method = 2NM, EM cycle = 2, Max-Change = 6.03157025822874 Method = KDE, EM cycle = 1, Max-Change = 6.09021485674526 Method = KDE, EM cycle = 2, Max-Change = 3.43644019346896 Method = DC, EM cycle = 1, Max-Change = 6.03970856872124 Method = DC, EM cycle = 2, Max-Change = 3.63753118756237 Method = LLS, EM cycle = 1, Max-Change = 6.06074579658812 Method = LLS, EM cycle = 2, Max-Change = 3.69138767250672 Method = N, EM cycle = 1, Max-Change = 4.89223679496234 Method = N, EM cycle = 2, Max-Change = 2.22208927517826 Method = N, EM cycle = 1, Max-Change = 4.89223679496234 Method = N, EM cycle = 2, Max-Change = 2.22208927517826 Method = EHM, EM cycle = 1, Max-Change = 1.466598916666 Method = EHM, EM cycle = 2, Max-Change = 0.211900842370132 Method = 2NM, EM cycle = 1, Max-Change = 1.47410887396381 Method = 2NM, EM cycle = 2, Max-Change = 0.209629532647032 Method = N, EM cycle = 1, Max-Change = 1.466598916666 Method = N, EM cycle = 2, Max-Change = 0.213146463826426Latent distribution is always normal distribution if "latent_dist = "Normal"" Method = EHM, EM cycle = 1, Max-Change = 1.45580780804904Convergence: Convergence failed. The Latent Distribution Estimation Method: EHM Class: dich For more information; Use 1) `$` sign for the direct access to the elements and/or 2) `summary` function for the briefly summarized output. Convergence: Convergence failed to meet the threshold of 0.5 within 1 iterations. Model Fit: deviance 4730.631 AIC 5004.631 BIC 5582.032 The Number of Parameters: item 18 dist 119 total 137 The Number of Items: dichotomous 9 polyotomous 0 The Estimated Latent Distribution: method - EHM ---------------------------------------- . @ @ @ @ . @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . +---------+---------+---------+---------+ -2 -1 0 1 2 Method = 2NM, EM cycle = 1, Max-Change = 2.0314989568934 Method = 2NM, EM cycle = 2, Max-Change = 0.297017484009591Convergence: Successfully converged. The Latent Distribution Estimation Method: 2NM Class: dich For more information; Use 1) `$` sign for the direct access to the elements and/or 2) `summary` function for the briefly summarized output. Convergence: Successfully converged below the threshold of 0.9 on 2nd iterations. Model Fit: deviance 4682.183 AIC 4706.183 BIC 4756.758 The Number of Parameters: item 9 dist 3 total 12 The Number of Items: dichotomous 9 polyotomous 0 The Estimated Latent Distribution: method - 2NM ---------------------------------------- . @ @ @ @ . . @ @ @ @ @ @ . @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . +---------+---------+---------+---------+ -2 -1 0 1 2 Method = N, EM cycle = 1, Max-Change = 2.00550507735081 Method = N, EM cycle = 2, Max-Change = 0.301466929681846Convergence: Successfully converged. The Latent Distribution Estimation Method: N Class: dich For more information; Use 1) `$` sign for the direct access to the elements and/or 2) `summary` function for the briefly summarized output. Convergence: Successfully converged below the threshold of 0.9 on 2nd iterations. Model Fit: deviance 4681.975 AIC 4699.975 BIC 4737.906 The Number of Parameters: item 9 dist 0 total 9 The Number of Items: dichotomous 9 polyotomous 0 The Estimated Latent Distribution: method - N ---------------------------------------- . . . @ @ @ @ @ . @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . +---------+---------+---------+---------+ -2 -1 0 1 2 Method = KDE, EM cycle = 1, Max-Change = 2.00550507735081 Method = KDE, EM cycle = 2, Max-Change = 0.287265910607939Convergence: Successfully converged. The Latent Distribution Estimation Method: KDE Class: dich For more information; Use 1) `$` sign for the direct access to the elements and/or 2) `summary` function for the briefly summarized output. Convergence: Successfully converged below the threshold of 0.9 on 2nd iterations. Model Fit: deviance 4690.301 AIC 4710.301 BIC 4752.447 The Number of Parameters: item 9 dist 1 total 10 The Number of Items: dichotomous 9 polyotomous 0 The Estimated Latent Distribution: method - KDE ---------------------------------------- . @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . @ @ @ @ @ @ @ @ @ @ @ @ . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . +---------+---------+---------+---------+ -2 -1 0 1 2 Method = DC, EM cycle = 1, Max-Change = 1.99549645656464 Method = DC, EM cycle = 2, Max-Change = 0.302332553508536Convergence: Convergence failed. The Latent Distribution Estimation Method: DC Class: dich For more information; Use 1) `$` sign for the direct access to the elements and/or 2) `summary` function for the briefly summarized output. Convergence: Convergence failed to meet the threshold of 1e-04 within 2 iterations. Model Fit: deviance 4683.121 AIC 4707.121 BIC 4757.696 The Number of Parameters: item 9 dist 3 total 12 The Number of Items: dichotomous 9 polyotomous 0 The Estimated Latent Distribution: method - DC ---------------------------------------- . . . . @ @ @ @ . @ @ @ @ @ @ @ . @ @ @ @ @ @ @ @ @ . @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . +---------+---------+---------+---------+ -2 -1 0 1 2 Insufficient data values to produce 10 bins for Item 1. 9 bins will be used. Insufficient data values to produce 9 bins for Item 1. 8 bins will be used. Insufficient data values to produce 10 bins for Item 2. 9 bins will be used. Insufficient data values to produce 9 bins for Item 2. 8 bins will be used. Insufficient data values to produce 10 bins for Item 3. 9 bins will be used. Insufficient data values to produce 9 bins for Item 3. 8 bins will be used. Insufficient data values to produce 10 bins for Item 4. 9 bins will be used. Insufficient data values to produce 9 bins for Item 4. 8 bins will be used. Insufficient data values to produce 10 bins for Item 5. 9 bins will be used. Insufficient data values to produce 9 bins for Item 5. 8 bins will be used. Insufficient data values to produce 10 bins for Item 6. 9 bins will be used. Insufficient data values to produce 9 bins for Item 6. 8 bins will be used. Insufficient data values to produce 10 bins for Item 7. 9 bins will be used. Insufficient data values to produce 9 bins for Item 7. 8 bins will be used. Insufficient data values to produce 10 bins for Item 8. 9 bins will be used. Insufficient data values to produce 9 bins for Item 8. 8 bins will be used. Insufficient data values to produce 10 bins for Item 9. 9 bins will be used. Insufficient data values to produce 9 bins for Item 9. 8 bins will be used. Insufficient data values to produce 10 bins for Item 1. 9 bins will be used. Insufficient data values to produce 9 bins for Item 1. 8 bins will be used. Insufficient data values to produce 10 bins for Item 2. 9 bins will be used. Insufficient data values to produce 9 bins for Item 2. 8 bins will be used. Insufficient data values to produce 10 bins for Item 3. 9 bins will be used. Insufficient data values to produce 9 bins for Item 3. 8 bins will be used. Insufficient data values to produce 10 bins for Item 4. 9 bins will be used. Insufficient data values to produce 9 bins for Item 4. 8 bins will be used. Insufficient data values to produce 10 bins for Item 5. 9 bins will be used. Insufficient data values to produce 9 bins for Item 5. 8 bins will be used. Insufficient data values to produce 10 bins for Item 6. 9 bins will be used. Insufficient data values to produce 9 bins for Item 6. 8 bins will be used. Insufficient data values to produce 10 bins for Item 7. 9 bins will be used. Insufficient data values to produce 9 bins for Item 7. 8 bins will be used. Insufficient data values to produce 10 bins for Item 8. 9 bins will be used. Insufficient data values to produce 9 bins for Item 8. 8 bins will be used. Insufficient data values to produce 10 bins for Item 9. 9 bins will be used. Insufficient data values to produce 9 bins for Item 9. 8 bins will be used. Method = N, EM cycle = 1, Max-Change = 4.06113185971103 Method = N, EM cycle = 2, Max-Change = 5.70089416832009Convergence: Convergence failed. The Latent Distribution Estimation Method: N Class: poly For more information; Use 1) `$` sign for the direct access to the elements and/or 2) `summary` function for the briefly summarized output. Convergence: Convergence failed to meet the threshold of 0.001 within 2 iterations. Model Fit: deviance 11606.18 AIC 11706.18 BIC 11916.91 The Number of Parameters: item 50 dist 0 total 50 The Number of Items: dichotomous 0 polyotomous 10 The Estimated Latent Distribution: method - N ---------------------------------------- . . . @ @ @ @ @ . @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . +---------+---------+---------+---------+ -2 -1 0 1 2 Latent distribution is always normal distribution if "latent_dist = "Normal"" Method = LLS, EM cycle = 1, Max-Change = 6.09021026462079 Method = LLS, EM cycle = 2, Max-Change = 3.337318597881Convergence: Convergence failed. The Latent Distribution Estimation Method: LLS Class: poly For more information; Use 1) `$` sign for the direct access to the elements and/or 2) `summary` function for the briefly summarized output. Convergence: Convergence failed to meet the threshold of 0.001 within 2 iterations. Model Fit: deviance 11857.29 AIC 11939.29 BIC 12112.09 The Number of Parameters: item 39 dist 2 total 41 The Number of Items: dichotomous 0 polyotomous 10 The Estimated Latent Distribution: method - LLS ---------------------------------------- . . . @ @ @ @ @ . @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . +---------+---------+---------+---------+ -2 -1 0 1 2 Method = N, EM cycle = 1, Max-Change = 6.38061382384528 Method = N, EM cycle = 2, Max-Change = 1.95531367162699Convergence: Convergence failed. The Latent Distribution Estimation Method: N Class: mix For more information; Use 1) `$` sign for the direct access to the elements and/or 2) `summary` function for the briefly summarized output. Convergence: Convergence failed to meet the threshold of 0.001 within 2 iterations. Model Fit: deviance 2484786 AIC 2484816 BIC 2484889 The Number of Parameters: item 15 dist 0 total 15 The Number of Items: dichotomous 5 polyotomous 5 The Estimated Latent Distribution: method - N ---------------------------------------- . . . @ @ @ @ @ . @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . +---------+---------+---------+---------+ -2 -1 0 1 2 Latent distribution is always normal distribution if "latent_dist = "Normal"" Method = N, EM cycle = 1, Max-Change = 2.55558861299848 Method = N, EM cycle = 2, Max-Change = 0.401356752406687Convergence: Convergence failed. The Latent Distribution Estimation Method: N Class: mix For more information; Use 1) `$` sign for the direct access to the elements and/or 2) `summary` function for the briefly summarized output. Convergence: Convergence failed to meet the threshold of 0.001 within 2 iterations. Model Fit: deviance 1883702 AIC 1883742 BIC 1883840 The Number of Parameters: item 20 dist 0 total 20 The Number of Items: dichotomous 5 polyotomous 5 The Estimated Latent Distribution: method - N ---------------------------------------- . . . @ @ @ @ @ . @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . . @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ . +---------+---------+---------+---------+ -2 -1 0 1 2 Latent distribution is always normal distribution if "latent_dist = "Normal"" [ FAIL 0 | WARN 19 | SKIP 1 | PASS 66 ] ══ Skipped tests (1) ═══════════════════════════════════════════════════════════ • empty test (1): 'test-summary_n_print.R:1:1' [ FAIL 0 | WARN 19 | SKIP 1 | PASS 66 ] > > proc.time() user system elapsed 14.14 2.39 16.54