Running 'testthat.R'
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 the 'metafor' package (version 3.0-2). 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......SSS
  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: ..............S.S....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_confint: 
  Checking misc: confint() function: ......
  misc_dfround: 
  Checking misc: dfround() function: ..
  misc_diagnostics_rma.mv: 
  Checking misc: model diagnostic functions for rma.mv(): SS
  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: .........
  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: SSS
  misc_plot_rma: 
  Checking misc: plot() function: ...
  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: 1SS
  misc_rma_handling_nas: 
  Checking misc: proper handling of missing values: S
  misc_rma_ls: 
  Checking misc: location-scale models: ......................................................................
  misc_rma_mv: 
  Checking misc: rma.mv() function: .....................2
  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: .S.S.S.S
  misc_setlab: 
  Checking misc: .setlab() function: .
  misc_tes: 
  Checking misc: tes() function: ..........
  misc_to_long_table_wide: 
  Checking misc: to.long() function: ......................
  misc_transf: 
  Checking misc: transformation functions: .......................
  misc_update: 
  Checking misc: update() function: ....S
  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: .S.S.S
  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: .S.S.S.
  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
  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(): ..........
  
  ══ 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:113:4) - Reason: On CRAN
  
  5. profiling works for the three-level random-effects model (multivariate parameterization). (test_analysis_example_konstantopoulos2011.r:147:4) - Reason: On CRAN
  
  6. BLUPs are calculated correctly for the three-level random-effects model (multilevel parameterization). (test_analysis_example_konstantopoulos2011.r:163:4) - Reason: On CRAN
  
  7. results are correct when allowing for different tau^2 per district. (test_analysis_example_konstantopoulos2011.r:179:4) - Reason: On CRAN
  
  8. results are correct for example 1. (test_analysis_example_law2016.r:9:4) - Reason: On CRAN
  
  9. results are correct for example 2. (test_analysis_example_law2016.r:84:4) - Reason: On CRAN
  
  10. back-transformations work as intended for individual studies and the model estimate. (test_analysis_example_miller1978.r:80:4) - Reason: On CRAN
  
  11. results are correct for the random-effects model. (test_analysis_example_raudenbush1985.r:40:4) - Reason: On CRAN
  
  12. results are correct for the mixed-effects model. (test_analysis_example_raudenbush1985.r:96:4) - Reason: On CRAN
  
  13. results are correct for Mantel-Haenszel method. (test_analysis_example_rothman2008.r:133:4) - Reason: On CRAN
  
  14. results are correct for Mantel-Haenszel method. (test_analysis_example_rothman2008.r:269:4) - Reason: On CRAN
  
  15. results are correct for Mantel-Haenszel method. (test_analysis_example_rothman2008.r:363:4) - Reason: On CRAN
  
  16. results for the binomial-normal normal are correct (measure=='PLO') (test_analysis_example_stijnen2010.r:40:4) - Reason: On CRAN
  
  17. results for the conditional logistic model with exact likelihood are correct (measure=='OR') (test_analysis_example_stijnen2010.r:83:4) - Reason: On CRAN
  
  18. results for the conditional logistic model with approximate likelihood are correct (measure=='OR') (test_analysis_example_stijnen2010.r:101:4) - Reason: On CRAN
  
  19. results for the Poisson-normal model are correct (measure=='IRLN') (test_analysis_example_stijnen2010.r:153:4) - Reason: On CRAN
  
  20. results for the Poisson-normal model are correct (measure=='IRR') (test_analysis_example_stijnen2010.r:196:4) - Reason: On CRAN
  
  21. the log likelihood plot can be created. (test_analysis_example_vanhouwelingen1993.r:14:4) - Reason: On CRAN
  
  22. results of the fixed-effects conditional logistic model are correct. (test_analysis_example_vanhouwelingen1993.r:25:4) - Reason: On CRAN
  
  23. results of the random-effects conditional logistic model are correct. (test_analysis_example_vanhouwelingen1993.r:50:4) - Reason: On CRAN
  
  24. profile plot for tau^2 can be drawn. (test_analysis_example_vanhouwelingen2002.r:65:4) - Reason: On CRAN
  
  25. forest plot of observed log(OR)s and corresponding BLUPs can be drawn. (test_analysis_example_vanhouwelingen2002.r:80:4) - Reason: On CRAN
  
  26. L'Abbe plot can be drawn. (test_analysis_example_vanhouwelingen2002.r:119:4) - Reason: On CRAN
  
  27. CI is correct for the profile likelihood method. (test_analysis_example_viechtbauer2007a.r:75:4) - Reason: On CRAN
  
  28. CI is correct for the parametric bootstrap method. (test_analysis_example_viechtbauer2007a.r:112:4) - Reason: On CRAN
  
  29. CI is correct for the non-parametric bootstrap method. (test_analysis_example_viechtbauer2007a.r:150:4) - Reason: On CRAN
  
  30. results are correct for the mixed-effects model. (test_analysis_example_viechtbauer2007b.r:78:4) - Reason: On CRAN
  
  31. log likelihood plot can be drawn. (test_analysis_example_yusuf1985.r:15:4) - Reason: On CRAN
  
  32. model diagnostic functions work with 'na.omit'. (test_misc_diagnostics_rma.mv.r:29:4) - Reason: On CRAN
  
  33. model diagnostic functions work with 'na.pass'. (test_misc_diagnostics_rma.mv.r:160:4) - Reason: On CRAN
  
  34. funnel() works correctly. (test_misc_funnel.r:11:4) - Reason: On CRAN
  
  35. 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
  
  36. 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
  
  37. permutest() gives correct results for a random-effects model. (test_misc_permutest.r:15:4) - Reason: On CRAN
  
  38. permutest() gives correct results for a mixed-effects model. (test_misc_permutest.r:58:4) - Reason: On CRAN
  
  39. permutest() gives correct results for example in Follmann & Proschan (1999). (test_misc_permutest.r:95:4) - Reason: On CRAN
  
  40. reporter() works correctly for 'rma.uni' objects. (test_misc_reporter.r:9:4) - Reason: On CRAN
  
  41. residuals are correct for rma.glmm(). (test_misc_residuals.r:86:4) - Reason: On CRAN
  
  42. rma.glmm() works correctly when using 'clogit' or 'clogistic'. (test_misc_rma_glmm.r:36:4) - Reason: On CRAN
  
  43. rma.glmm() works correctly when using 'nlminb' or 'minqa'. (test_misc_rma_glmm.r:54:4) - Reason: On CRAN
  
  44. rma.glmm() handles NAs correctly. (test_misc_rma_handling_nas.r:9:4) - Reason: On CRAN
  
  45. results are correct for a step function model. (test_misc_selmodel.r:11:4) - Reason: On CRAN
  
  46. results are correct for the beta function model. (test_misc_selmodel.r:41:4) - Reason: On CRAN
  
  47. results are correct for the various exponential function models. (test_misc_selmodel.r:86:4) - Reason: On CRAN
  
  48. results are correct for a pirori chosen step function models. (test_misc_selmodel.r:140:4) - Reason: On CRAN
  
  49. update() works for rma.glmm(). (test_misc_update.r:47:4) - Reason: On CRAN
  
  50. plot can be drawn. (test_plots_baujat_plot.r:11:4) - Reason: On CRAN
  
  51. plot can be drawn. (test_plots_caterpillar_plot.r:11:4) - Reason: On CRAN
  
  52. plot can be drawn. (test_plots_contour-enhanced_funnel_plot.r:11:4) - Reason: On CRAN
  
  53. plot can be drawn for 'rma.uni' object. (test_plots_cumulative_forest_plot.r:11:4) - Reason: On CRAN
  
  54. plot can be drawn for 'rma.mh' object. (test_plots_cumulative_forest_plot.r:42:4) - Reason: On CRAN
  
  55. plot can be drawn for 'rma.peto' object. (test_plots_cumulative_forest_plot.r:70:4) - Reason: On CRAN
  
  56. plot can be drawn. (test_plots_forest_plot_with_subgroups.r:11:4) - Reason: On CRAN
  
  57. plot can be drawn. (test_plots_funnel_plot_variations.r:11:4) - Reason: On CRAN
  
  58. plot can be drawn. (test_plots_funnel_plot_with_trim_and_fill.r:11:4) - Reason: On CRAN
  
  59. plot can be drawn. (test_plots_gosh.r:11:4) - Reason: On CRAN
  
  60. plot can be drawn. (test_plots_labbe_plot.r:11:4) - Reason: On CRAN
  
  61. plot can be drawn. (test_plots_llplot.r:11:4) - Reason: On CRAN
  
  62. plot can be drawn. (test_plots_meta-analytic_scatterplot.r:11:4) - Reason: On CRAN
  
  63. plot can be drawn for 'rma.uni' object. (test_plots_normal_qq_plots.r:11:4) - Reason: On CRAN
  
  64. plot can be drawn for 'rma.mh' object. (test_plots_normal_qq_plots.r:49:4) - Reason: On CRAN
  
  65. plot can be drawn for 'rma.peto' object. (test_plots_normal_qq_plots.r:64:4) - Reason: On CRAN
  
  66. plot can be drawn. (test_plots_plot_of_cumulative_results.r:11:4) - Reason: On CRAN
  
  67. plot can be drawn. (test_plots_plot_of_influence_diagnostics.r:11:4) - Reason: On CRAN
  
  68. plot can be drawn. (test_plots_radial_plot.r:11:4) - Reason: On CRAN
  
  ══ Failed ══════════════════════════════════════════════════════════════════════
  ── 1. Error (test_misc_rma_glmm.r:11:4): rma.glmm() works correctly for 'UM.RS' 
  Error in `rma.glmm(measure = "OR", ai = ai, n1i = n1i, ci = ci, n2i = n2i, 
      data = dat, model = "UM.RS", method = "FE")`: Please install the 'lme4' package to fit this model.
  Backtrace:
   1. testthat::expect_warning(...) test_misc_rma_glmm.r:11:3
   6. metafor::rma.glmm(...)
  
  ── 2. Error (test_misc_rma_mv.r:110:4): rma.mv() works correctly with different 
  Error in `rma.mv(yi, vi, random = ~1 | trial, data = dat, control = list(optimizer = "nloptr"))`: Please install the 'nloptr' package to use this optimizer.
  Backtrace:
   1. metafor::rma.mv(yi, vi, random = ~1 | trial, data = dat, control = list(optimizer = "nloptr")) test_misc_rma_mv.r:110:3
  
  ══ DONE ════════════════════════════════════════════════════════════════════════
  Error: Test failures
  Execution halted