Running ‘testthat.R’ [79s/110s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > ### to also run skip_on_cran() tests, uncomment:
  > #Sys.setenv(NOT_CRAN="true")
  > 
  > library(testthat)
  > library(metafor)
  Loading required package: Matrix
  Loading required package: metadat
  Loading required package: numDeriv
  
  Loading the 'metafor' package (version 5.0-1). For an
  introduction to the package please type: help(metafor)
  
  > test_check("metafor", reporter="summary")
  analysis_example_berkey1995: 
  Checking analysis example: berkey1995: ............
  analysis_example_berkey1998: 
  Checking analysis example: berkey1998: ..............
  analysis_example_dersimonian2007: 
  Checking analysis example: dersimonian2007: S
  analysis_example_gleser2009: 
  Checking analysis example: gleser2009: .......................
  analysis_example_henmi2010: 
  Checking analysis example: henmi2010: .......
  analysis_example_ishak2007: 
  Checking analysis example: ishak2007: .......................
  analysis_example_jackson2014: 
  Checking analysis example: jackson2014: SS
  analysis_example_konstantopoulos2011: 
  Checking analysis example: konstantopoulos2011: .............................S.....SSSS
  analysis_example_law2016: 
  Checking analysis example: law2016: SS
  analysis_example_lipsey2001: 
  Checking analysis example: lipsey2001: ..........................
  analysis_example_miller1978: 
  Checking analysis example: miller1978: ...........S
  analysis_example_morris2008: 
  Checking analysis example: morris2008: ..............
  analysis_example_normand1999: 
  Checking analysis example: normand1999: ..............................
  analysis_example_raudenbush1985: 
  Checking analysis example: raudenbush1985: ..........S.............S
  analysis_example_raudenbush2009: 
  Checking analysis example: raudenbush2009: ..................
  analysis_example_rothman2008: 
  Checking analysis example: rothman2008: .............................S.....................S..............S
  analysis_example_stijnen2010: 
  Checking analysis example: stijnen2010: ............S.......SS............S......S
  analysis_example_vanhouwelingen1993: 
  Checking analysis example: vanhouwelingen1993: SSS
  analysis_example_vanhouwelingen2002: 
  Checking analysis example: vanhouwelingen2002: .............SS...S...............................
  analysis_example_viechtbauer2005: 
  Checking analysis example: viechtbauer2005: ........
  analysis_example_viechtbauer2007a: 
  Checking analysis example: viechtbauer2007a: .......S...SS
  analysis_example_viechtbauer2007b: 
  Checking analysis example: viechtbauer2007b: ............S
  analysis_example_yusuf1985: 
  Checking analysis example: yusuf1985: S.....
  misc_aggregate: 
  Checking misc: aggregate() function: ..............
  misc_anova: 
  Checking misc: anova() function: ..........................
  misc_calc_q: 
  Checking misc: computation of Q-test: ..........
  misc_coef_se: 
  Checking misc: coef() and se() functions: ................
  misc_confint: 
  Checking misc: confint() function: .......
  misc_cumul: 
  Checking misc: cumul() functions: .........
  misc_dfround: 
  Checking misc: dfround() function: ..
  misc_diagnostics_rma.mv: 
  Checking misc: model diagnostic functions for rma.mv(): SS
  misc_emmprep: 
  Checking misc: emmprep() function: SSS
  misc_escalc: 
  Checking misc: escalc() function: .........................................................................................................................
  misc_fitstats: 
  Checking misc: computations of fit statistics: .......................
  misc_formula: 
  Checking misc: formula() function: .......
  misc_fsn: 
  Checking misc: fsn() function: .....S....S....S
  misc_funnel: 
  Checking misc: funnel() functions: S
  misc_handling_nas: 
  Checking misc: handling of NAs: ......................................................................................
  misc_handling_of_edge_cases_due_to_zeros: 
  Checking misc: handling of edge cases due to zeros: .......S.......S
  misc_influence: 
  Checking misc: influence() and related functions: .........................
  misc_list_rma: 
  Checking misc: head.list.rma() and tail.list.rma() functions: ....
  misc_matreg: 
  Checking misc: matreg() function: ..................................................
  misc_metan_vs_rma.mh_with_dat.bcg: 
  Checking misc: rma.mh() against metan with 'dat.bcg': .....................
  misc_metan_vs_rma.peto_with_dat.bcg: 
  Checking misc: rma.peto() against metan with 'dat.bcg': ........
  misc_metan_vs_rma.uni_with_dat.bcg: 
  Checking misc: rma.uni() against metan with 'dat.bcg': .............................................
  misc_pdfs: 
  Checking misc: pdfs of various measures: .....
  misc_permutest: 
  Checking misc: permutest() function: SSSS
  misc_plot_rma: 
  Checking misc: plot() function: SSS
  misc_predict: 
  Checking misc: predict() function: ..................................
  misc_pub_bias: 
  Checking misc: regtest() and ranktest() functions: ............
  misc_replmiss: 
  Checking misc: replmiss() function: ...
  misc_reporter: 
  Checking misc: reporter() function: .S
  misc_residuals: 
  Checking misc: residuals() function: .....................S
  misc_rma_error_handling: 
  Checking misc: proper handling of errors in rma(): ......
  misc_rma_glmm: 
  Checking misc: rma.glmm() function: ...1............SSS
  misc_rma_handling_nas: 
  Checking misc: proper handling of missing values: S
  misc_rma_ls: 
  Checking misc: location-scale models: ...........SSSSSSSS
  misc_rma_mv: 
  Checking misc: rma.mv() function: ..............S...
  misc_rma_uni: 
  Checking misc: rma() function: ..............
  misc_rma_uni_ls: 
  Checking misc: rma() function with location-scale models: ...............
  misc_rma_vs_direct_computation: 
  Checking misc: rma.uni() against direct computations: .....
  misc_rma_vs_lm: 
  Checking tip: rma() results match up with those from lm(): ........
  misc_robust: 
  Checking misc: robust() function: ..........................................................................
  misc_selmodel: 
  Checking misc: selmodel() function: SSSSS
  misc_setlab: 
  Checking misc: .setlab() function: S
  misc_tes: 
  Checking misc: tes() function: ......S
  misc_to_long_table_wide: 
  Checking misc: to.long() function: ......................
  misc_transf: 
  Checking misc: transformation functions: .......................
  misc_update: 
  Checking misc: update() function: ....S
  misc_vcalc: 
  Checking misc: vcalc() function: ......
  misc_vcov: 
  Checking misc: vcov() function: ........
  misc_vec2mat: 
  Checking misc: vec2mat() function: ....
  misc_vif: 
  Checking misc: vif() function: ...
  misc_weights: 
  Checking misc: weights() function: ..........................
  plots_baujat_plot: 
  Checking plots example: Baujat plot: S
  plots_caterpillar_plot: 
  Checking plots example: caterpillar plot: S
  plots_contour-enhanced_funnel_plot: 
  Checking plots example: contour-enhanced funnel plot: S
  plots_cumulative_forest_plot: 
  Checking plots example: cumulative forest plot: SSS
  plots_forest_plot_with_predstyle: 
  Checking plots example: forest plot with adjusted predstyle: SSSSS
  plots_forest_plot_with_subgroups: 
  Checking plots example: forest plot with subgroups: S
  plots_funnel_plot_variations: 
  Checking plots example: funnel plot variations: S
  plots_funnel_plot_with_trim_and_fill: 
  Checking plots example: funnel plot with trim and fill: S
  plots_gosh: 
  Checking plots example: GOSH plot: S
  plots_labbe_plot: 
  Checking plots example: L'Abbe plot: S
  plots_llplot: 
  Checking plots example: likelihood plot: S
  plots_meta-analytic_scatterplot: 
  Checking plots example: meta-analytic scatterplot: S
  plots_normal_qq_plots: 
  Checking plots example: normal QQ plots: SSS.
  plots_plot_of_cumulative_results: 
  Checking plots example: plot of cumulative results: S
  plots_plot_of_influence_diagnostics: 
  Checking plots example: plot of influence diagnostics: S
  plots_radial_plot: 
  Checking plots example: radial (Galbraith) plot: S
  plots_regplot: 
  Checking plots example: scatter/bubble plot: S
  tips_model_selection_with_glmulti_and_mumin: 
  Checking tip: model selection using the glmulti and MuMIn packages: SS
  tips_multiple_imputation_with_mice: 
  Checking tip: multiple imputation with the mice and metafor packages: SS
  tips_regression_with_rma: 
  Checking tip: rma() results match up with those from lm(): ...........
  tips_rma_vs_lm_and_lme: 
  Checking tip: rma() results match up with those from lm() and lme(): ..........
  tips_testing_factors_lincoms: 
  Checking tip: testing factors and linear combinations of parameters: ............................
  
  ══ Skipped ═════════════════════════════════════════════════════════════════════
  1. results are correct for the CLASP example. ('test_analysis_example_dersimonian2007.r:17:4') - Reason: On CRAN
  
  2. confint() gives correct results for example 1 in Jackson et al. (2014). ('test_analysis_example_jackson2014.r:9:4') - Reason: On CRAN
  
  3. confint() gives correct results for example 2 in Jackson et al. (2014). ('test_analysis_example_jackson2014.r:49:4') - Reason: On CRAN
  
  4. profiling works for the three-level random-effects model (multilevel parameterization). ('test_analysis_example_konstantopoulos2011.r:117:4') - Reason: On CRAN
  
  5. profiling works for the three-level random-effects model (multivariate parameterization). ('test_analysis_example_konstantopoulos2011.r:162:4') - Reason: On CRAN
  
  6. BLUPs are calculated correctly for the three-level random-effects model (multilevel parameterization). ('test_analysis_example_konstantopoulos2011.r:191:4') - Reason: On CRAN
  
  7. restarting with 'restart=TRUE' works. ('test_analysis_example_konstantopoulos2011.r:207:4') - Reason: On CRAN
  
  8. results are correct when allowing for different tau^2 per district. ('test_analysis_example_konstantopoulos2011.r:221:4') - Reason: On CRAN
  
  9. results are correct for example 1. ('test_analysis_example_law2016.r:9:4') - Reason: On CRAN
  
  10. results are correct for example 2. ('test_analysis_example_law2016.r:86:4') - Reason: On CRAN
  
  11. back-transformations work as intended for individual studies and the model estimate. ('test_analysis_example_miller1978.r:80:4') - Reason: On CRAN
  
  12. results are correct for the random-effects model. ('test_analysis_example_raudenbush1985.r:40:4') - Reason: On CRAN
  
  13. results are correct for the mixed-effects model. ('test_analysis_example_raudenbush1985.r:102:4') - Reason: On CRAN
  
  14. results are correct for Mantel-Haenszel method. ('test_analysis_example_rothman2008.r:133:4') - Reason: On CRAN
  
  15. results are correct for Mantel-Haenszel method. ('test_analysis_example_rothman2008.r:269:4') - Reason: On CRAN
  
  16. results are correct for Mantel-Haenszel method. ('test_analysis_example_rothman2008.r:363:4') - Reason: On CRAN
  
  17. results for the binomial-normal normal are correct (measure=='PLO') ('test_analysis_example_stijnen2010.r:40:4') - Reason: On CRAN
  
  18. results for the conditional logistic model with exact likelihood are correct (measure=='OR') ('test_analysis_example_stijnen2010.r:83:4') - Reason: On CRAN
  
  19. results for the conditional logistic model with approximate likelihood are correct (measure=='OR') ('test_analysis_example_stijnen2010.r:101:4') - Reason: On CRAN
  
  20. results for the Poisson-normal model are correct (measure=='IRLN') ('test_analysis_example_stijnen2010.r:153:4') - Reason: On CRAN
  
  21. results for the Poisson-normal model are correct (measure=='IRR') ('test_analysis_example_stijnen2010.r:196:4') - Reason: On CRAN
  
  22. the log likelihood plot can be created. ('test_analysis_example_vanhouwelingen1993.r:14:4') - Reason: On CRAN
  
  23. results of the equal-effects conditional logistic model are correct. ('test_analysis_example_vanhouwelingen1993.r:38:4') - Reason: On CRAN
  
  24. results of the random-effects conditional logistic model are correct. ('test_analysis_example_vanhouwelingen1993.r:63:4') - Reason: On CRAN
  
  25. profile plot for tau^2 can be drawn. ('test_analysis_example_vanhouwelingen2002.r:63:4') - Reason: On CRAN
  
  26. forest plot of observed log(OR)s and corresponding BLUPs can be drawn. ('test_analysis_example_vanhouwelingen2002.r:78:4') - Reason: On CRAN
  
  27. L'Abbe plot can be drawn. ('test_analysis_example_vanhouwelingen2002.r:130:4') - Reason: On CRAN
  
  28. CI is correct for the profile likelihood method. ('test_analysis_example_viechtbauer2007a.r:79:4') - Reason: On CRAN
  
  29. CI is correct for the parametric bootstrap method. ('test_analysis_example_viechtbauer2007a.r:121:4') - Reason: On CRAN
  
  30. CI is correct for the non-parametric bootstrap method. ('test_analysis_example_viechtbauer2007a.r:159:4') - Reason: On CRAN
  
  31. results are correct for the mixed-effects model. ('test_analysis_example_viechtbauer2007b.r:74:4') - Reason: On CRAN
  
  32. log likelihood plot can be drawn. ('test_analysis_example_yusuf1985.r:15:4') - Reason: On CRAN
  
  33. model diagnostic functions work with 'na.omit'. ('test_misc_diagnostics_rma.mv.r:29:4') - Reason: On CRAN
  
  34. model diagnostic functions work with 'na.pass'. ('test_misc_diagnostics_rma.mv.r:160:4') - Reason: On CRAN
  
  35. emmprep() gives correct results for an intercept-only model. ('test_misc_emmprep.r:16:4') - Reason: On CRAN
  
  36. emmprep() gives correct results for a meta-regression model. ('test_misc_emmprep.r:36:4') - Reason: On CRAN
  
  37. emmprep() gives correct results for the r-to-z transformation. ('test_misc_emmprep.r:63:4') - Reason: On CRAN
  
  38. confint() gives correct results for the 'expectancy data' in Becker (2005). ('test_misc_fsn.r:33:4') - Reason: On CRAN
  
  39. confint() gives correct results for the 'passive smoking data' in Becker (2005). ('test_misc_fsn.r:65:4') - Reason: On CRAN
  
  40. confint() gives correct results for the 'interview data' in Becker (2005). ('test_misc_fsn.r:93:4') - Reason: On CRAN
  
  41. funnel() works correctly. ('test_misc_funnel.r:9:4') - Reason: On CRAN
  
  42. rma.peto(), rma.mh(), and rma.glmm() handle outcome1 never occurring properly. ('test_misc_handling_of_edge_cases_due_to_zeros.r:23:4') - Reason: On CRAN
  
  43. rma.peto(), rma.mh(), and rma.glmm() handle outcome2 never occurring properly. ('test_misc_handling_of_edge_cases_due_to_zeros.r:45:4') - Reason: On CRAN
  
  44. permutest() gives correct results for a random-effects model. ('test_misc_permutest.r:15:4') - Reason: On CRAN
  
  45. permutest() gives correct results for a mixed-effects model. ('test_misc_permutest.r:44:4') - Reason: On CRAN
  
  46. permutest() gives correct results for example in Follmann & Proschan (1999). ('test_misc_permutest.r:68:4') - Reason: On CRAN
  
  47. permutest() works correctly when specifying the 'btt' argument. ('test_misc_permutest.r:95:4') - Reason: On CRAN
  
  48. plot can be drawn for rma(). ('test_misc_plot_rma.r:9:4') - Reason: On CRAN
  
  49. plot can be drawn for rma.mh(). ('test_misc_plot_rma.r:48:4') - Reason: On CRAN
  
  50. plot can be drawn for rma.peto(). ('test_misc_plot_rma.r:70:4') - Reason: On CRAN
  
  51. reporter() works correctly for 'rma.uni' objects. ('test_misc_reporter.r:12:4') - Reason: On CRAN
  
  52. residuals are correct for rma.glmm(). ('test_misc_residuals.r:81:4') - Reason: On CRAN
  
  53. rma.glmm() works correctly for 'UM.RS' model. ('test_misc_rma_glmm.r:69:4') - Reason: On CRAN
  
  54. rma.glmm() works correctly when using 'clogit' or 'clogistic'. ('test_misc_rma_glmm.r:89:4') - Reason: On CRAN
  
  55. rma.glmm() works correctly for 'CM.EL' model. ('test_misc_rma_glmm.r:107:4') - Reason: On CRAN
  
  56. rma.glmm() handles NAs correctly. ('test_misc_rma_handling_nas.r:9:4') - Reason: On CRAN
  
  57. location-scale model works correctly for two subgroups with different tau^2 values ('test_misc_rma_ls.r:38:4') - Reason: On CRAN
  
  58. profile() and confint() work correctly for location-scale models ('test_misc_rma_ls.r:49:4') - Reason: On CRAN
  
  59. location-scale model works correctly for a continuous predictor ('test_misc_rma_ls.r:92:4') - Reason: On CRAN
  
  60. location-scale model works correctly for multiple predictors ('test_misc_rma_ls.r:155:4') - Reason: On CRAN
  
  61. permutation tests work correctly for a location-scale model ('test_misc_rma_ls.r:200:4') - Reason: On CRAN
  
  62. predict() works correctly for location-scale models ('test_misc_rma_ls.r:230:4') - Reason: On CRAN
  
  63. anova() works correctly for location-scale models ('test_misc_rma_ls.r:281:4') - Reason: On CRAN
  
  64. vif() works correctly for location-scale models ('test_misc_rma_ls.r:322:4') - Reason: On CRAN
  
  65. rma.mv() works correctly with different optimizers ('test_misc_rma_mv.r:94:4') - Reason: On CRAN
  
  66. results are correct for a step function model. ('test_misc_selmodel.r:9:4') - Reason: On CRAN
  
  67. results are correct for the beta function model. ('test_misc_selmodel.r:59:4') - Reason: On CRAN
  
  68. results are correct for the various exponential function models. ('test_misc_selmodel.r:114:4') - Reason: On CRAN
  
  69. results are correct for a pirori chosen step function models. ('test_misc_selmodel.r:170:4') - Reason: On CRAN
  
  70. results are correct for a truncated distribution model. ('test_misc_selmodel.r:192:4') - Reason: On CRAN
  
  71. .setlab() works correctly together with forest(). ('test_misc_setlab.r:12:4') - Reason: On CRAN
  
  72. tes() works correctly for 'dat.dorn2007'. ('test_misc_tes.r:25:4') - Reason: On CRAN
  
  73. update() works for rma.glmm(). ('test_misc_update.r:45:4') - Reason: On CRAN
  
  74. plot can be drawn. ('test_plots_baujat_plot.r:11:4') - Reason: On CRAN
  
  75. plot can be drawn. ('test_plots_caterpillar_plot.r:11:4') - Reason: On CRAN
  
  76. plot can be drawn. ('test_plots_contour-enhanced_funnel_plot.r:11:4') - Reason: On CRAN
  
  77. plot can be drawn for 'rma.uni' object. ('test_plots_cumulative_forest_plot.r:11:4') - Reason: On CRAN
  
  78. plot can be drawn for 'rma.mh' object. ('test_plots_cumulative_forest_plot.r:39:4') - Reason: On CRAN
  
  79. plot can be drawn for 'rma.peto' object. ('test_plots_cumulative_forest_plot.r:64:4') - Reason: On CRAN
  
  80. plot can be drawn with predstyle='l'. ('test_plots_forest_plot_with_predstyle.r:15:4') - Reason: On CRAN
  
  81. plot can be drawn with predstyle='b'. ('test_plots_forest_plot_with_predstyle.r:75:4') - Reason: On CRAN
  
  82. plot can be drawn with predstyle='s'. ('test_plots_forest_plot_with_predstyle.r:135:4') - Reason: On CRAN
  
  83. plot can be drawn with predstyle='d'. ('test_plots_forest_plot_with_predstyle.r:195:4') - Reason: On CRAN
  
  84. plot can be drawn with predstyle='d' and transf=exp. ('test_plots_forest_plot_with_predstyle.r:255:4') - Reason: On CRAN
  
  85. plot can be drawn. ('test_plots_forest_plot_with_subgroups.r:11:4') - Reason: On CRAN
  
  86. plot can be drawn. ('test_plots_funnel_plot_variations.r:11:4') - Reason: On CRAN
  
  87. plot can be drawn. ('test_plots_funnel_plot_with_trim_and_fill.r:11:4') - Reason: On CRAN
  
  88. plot can be drawn. ('test_plots_gosh.r:11:4') - Reason: On CRAN
  
  89. plot can be drawn. ('test_plots_labbe_plot.r:11:4') - Reason: On CRAN
  
  90. plot can be drawn. ('test_plots_llplot.r:9:4') - Reason: On CRAN
  
  91. plot can be drawn. ('test_plots_meta-analytic_scatterplot.r:11:4') - Reason: On CRAN
  
  92. plot can be drawn for 'rma.uni' object. ('test_plots_normal_qq_plots.r:11:4') - Reason: On CRAN
  
  93. plot can be drawn for 'rma.mh' object. ('test_plots_normal_qq_plots.r:50:4') - Reason: On CRAN
  
  94. plot can be drawn for 'rma.peto' object. ('test_plots_normal_qq_plots.r:66:4') - Reason: On CRAN
  
  95. plot can be drawn. ('test_plots_plot_of_cumulative_results.r:11:4') - Reason: On CRAN
  
  96. plot can be drawn. ('test_plots_plot_of_influence_diagnostics.r:11:4') - Reason: On CRAN
  
  97. plot can be drawn. ('test_plots_radial_plot.r:11:4') - Reason: On CRAN
  
  98. plot can be drawn. ('test_plots_regplot.r:11:4') - Reason: On CRAN
  
  99. results are correct for package glmulti. ('test_tips_model_selection_with_glmulti_and_mumin.r:16:4') - Reason: On CRAN
  
  100. results are correct for package MuMIn. ('test_tips_model_selection_with_glmulti_and_mumin.r:89:4') - Reason: On CRAN
  
  101. results are correct for package mice. ('test_tips_multiple_imputation_with_mice.r:16:4') - Reason: On CRAN
  
  102. results are correct for package Amelia. ('test_tips_multiple_imputation_with_mice.r:59:4') - Reason: On CRAN
  
  ══ Failed ══════════════════════════════════════════════════════════════════════
  ── 1. Error ('test_misc_rma_glmm.r:17:4'): rma.glmm() works correctly for 'UM.FS
  Error in `rma.glmm(measure = "OR", ai = ai, n1i = n1i, ci = ci, n2i = n2i, data = dat, model = "UM.FS", test = "t")`: Cannot fit ML model (set 'verbose=TRUE' to obtain further details).
  Backtrace:
      ▆
   1. ├─testthat::expect_warning(...) at test_misc_rma_glmm.r:17:4
   2. │ └─testthat:::quasi_capture(...)
   3. │   ├─testthat (local) .capture(...)
   4. │   │ └─base::withCallingHandlers(...)
   5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
   6. └─metafor::rma.glmm(...)
  
  ══ DONE ════════════════════════════════════════════════════════════════════════
  Error:
  ! Test failures.
  Execution halted