Last updated on 2024-11-02 23:48:33 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 4.6-0 | 67.28 | 425.59 | 492.87 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 4.6-0 | 42.17 | 250.58 | 292.75 | NOTE | |
| r-devel-linux-x86_64-fedora-clang | 4.6-0 | 806.83 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 4.6-0 | 799.59 | OK | |||
| r-devel-windows-x86_64 | 4.6-0 | 67.00 | 370.00 | 437.00 | NOTE | |
| r-patched-linux-x86_64 | 4.6-0 | 73.12 | 388.31 | 461.43 | OK | |
| r-release-linux-x86_64 | 4.6-0 | 67.46 | 373.18 | 440.64 | ERROR | |
| r-release-macos-arm64 | 4.6-0 | 159.00 | NOTE | |||
| r-release-macos-x86_64 | 4.6-0 | 280.00 | NOTE | |||
| r-release-windows-x86_64 | 4.6-0 | 65.00 | 380.00 | 445.00 | NOTE | |
| r-oldrel-macos-arm64 | 4.6-0 | 166.00 | NOTE | |||
| r-oldrel-macos-x86_64 | 4.6-0 | 498.00 | NOTE | |||
| r-oldrel-windows-x86_64 | 4.6-0 | 87.00 | 499.00 | 586.00 | NOTE |
Version: 4.6-0
Check: Rd cross-references
Result: NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
misc-options.Rd: dat.moura2021
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-windows-x86_64
Version: 4.6-0
Check: package dependencies
Result: NOTE
Packages suggested but not available for checking:
'lme4', 'minqa', 'lbfgsb3c', 'Epi', 'glmmTMB', 'ape'
Flavor: r-release-linux-x86_64
Version: 4.6-0
Check: examples
Result: ERROR
Running examples in ‘metafor-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: update.rma
> ### Title: Model Updating for 'rma' Objects
> ### Aliases: update update.rma
> ### Keywords: models
>
> ### ** Examples
>
> ### calculate log risk ratios and corresponding sampling variances
> dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)
>
> ### fit random-effects model (method="REML" is default)
> res <- rma(yi, vi, data=dat, digits=3)
> res
Random-Effects Model (k = 13; tau^2 estimator: REML)
tau^2 (estimated amount of total heterogeneity): 0.313 (SE = 0.166)
tau (square root of estimated tau^2 value): 0.560
I^2 (total heterogeneity / total variability): 92.22%
H^2 (total variability / sampling variability): 12.86
Test for Heterogeneity:
Q(df = 12) = 152.233, p-val < .001
Model Results:
estimate se zval pval ci.lb ci.ub
-0.715 0.180 -3.974 <.001 -1.067 -0.362 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> ### fit mixed-effects model with two moderators (absolute latitude and publication year)
> res <- update(res, ~ ablat + year)
> res
Mixed-Effects Model (k = 13; tau^2 estimator: REML)
tau^2 (estimated amount of residual heterogeneity): 0.111 (SE = 0.084)
tau (square root of estimated tau^2 value): 0.333
I^2 (residual heterogeneity / unaccounted variability): 71.98%
H^2 (unaccounted variability / sampling variability): 3.57
R^2 (amount of heterogeneity accounted for): 64.63%
Test for Residual Heterogeneity:
QE(df = 10) = 28.325, p-val = 0.002
Test of Moderators (coefficients 2:3):
QM(df = 2) = 12.204, p-val = 0.002
Model Results:
estimate se zval pval ci.lb ci.ub
intrcpt -3.546 29.096 -0.122 0.903 -60.572 53.481
ablat -0.028 0.010 -2.737 0.006 -0.048 -0.008 **
year 0.002 0.015 0.130 0.897 -0.027 0.031
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> ### remove 'year' moderator
> res <- update(res, ~ . - year)
> res
Mixed-Effects Model (k = 13; tau^2 estimator: REML)
tau^2 (estimated amount of residual heterogeneity): 0.076 (SE = 0.059)
tau (square root of estimated tau^2 value): 0.276
I^2 (residual heterogeneity / unaccounted variability): 68.39%
H^2 (unaccounted variability / sampling variability): 3.16
R^2 (amount of heterogeneity accounted for): 75.62%
Test for Residual Heterogeneity:
QE(df = 11) = 30.733, p-val = 0.001
Test of Moderators (coefficient 2):
QM(df = 1) = 16.357, p-val < .001
Model Results:
estimate se zval pval ci.lb ci.ub
intrcpt 0.251 0.249 1.009 0.313 -0.237 0.740
ablat -0.029 0.007 -4.044 <.001 -0.043 -0.015 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> ### fit model with ML estimation
> update(res, method="ML")
Mixed-Effects Model (k = 13; tau^2 estimator: ML)
tau^2 (estimated amount of residual heterogeneity): 0.034 (SE = 0.028)
tau (square root of estimated tau^2 value): 0.185
I^2 (residual heterogeneity / unaccounted variability): 49.33%
H^2 (unaccounted variability / sampling variability): 1.97
R^2 (amount of heterogeneity accounted for): 87.73%
Test for Residual Heterogeneity:
QE(df = 11) = 30.733, p-val = 0.001
Test of Moderators (coefficient 2):
QM(df = 1) = 28.911, p-val < .001
Model Results:
estimate se zval pval ci.lb ci.ub
intrcpt 0.282 0.187 1.507 0.132 -0.085 0.649
ablat -0.030 0.005 -5.377 <.001 -0.040 -0.019 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> ### example with rma.glmm()
> res <- rma.glmm(measure="OR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, digits=3)
Error in rma.glmm(measure = "OR", ai = tpos, bi = tneg, ci = cpos, di = cneg, :
Please install the 'lme4' package to fit this model.
Execution halted
Flavor: r-release-linux-x86_64
Version: 4.6-0
Check: tests
Result: ERROR
Running ‘testthat.R’ [44s/61s]
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 4.6-0). 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: ..............S.S....S.........................
analysis_example_viechtbauer2005:
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analysis_example_viechtbauer2007a:
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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_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_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: SSS
misc_plot_rma:
Checking misc: plot() function: .S.S.S
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: ...12SS
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: ..................3..
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.S
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: .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
plots_regplot:
Checking plots example: scatter/bubble 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:119:4') - Reason: On CRAN
5. profiling works for the three-level random-effects model (multivariate parameterization). ('test_analysis_example_konstantopoulos2011.r:156:4') - Reason: On CRAN
6. BLUPs are calculated correctly for the three-level random-effects model (multilevel parameterization). ('test_analysis_example_konstantopoulos2011.r:174:4') - Reason: On CRAN
7. restarting with 'restart=TRUE' works. ('test_analysis_example_konstantopoulos2011.r:190:4') - Reason: On CRAN
8. results are correct when allowing for different tau^2 per district. ('test_analysis_example_konstantopoulos2011.r:204:4') - 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:28:4') - Reason: On CRAN
24. results of the random-effects conditional logistic model are correct. ('test_analysis_example_vanhouwelingen1993.r:53:4') - Reason: On CRAN
25. profile plot for tau^2 can be drawn. ('test_analysis_example_vanhouwelingen2002.r:65:4') - Reason: On CRAN
26. forest plot of observed log(OR)s and corresponding BLUPs can be drawn. ('test_analysis_example_vanhouwelingen2002.r:82:4') - Reason: On CRAN
27. L'Abbe plot can be drawn. ('test_analysis_example_vanhouwelingen2002.r:123:4') - 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:11:4') - 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:45:4') - Reason: On CRAN
46. permutest() gives correct results for example in Follmann & Proschan (1999). ('test_misc_permutest.r:69:4') - Reason: On CRAN
47. plot can be drawn for rma(). ('test_misc_plot_rma.r:11:4') - Reason: On CRAN
48. plot can be drawn for rma.mh(). ('test_misc_plot_rma.r:36:4') - Reason: On CRAN
49. plot can be drawn for rma.peto(). ('test_misc_plot_rma.r:52:4') - Reason: On CRAN
50. reporter() works correctly for 'rma.uni' objects. ('test_misc_reporter.r:12:4') - Reason: On CRAN
51. residuals are correct for rma.glmm(). ('test_misc_residuals.r:81:4') - Reason: On CRAN
52. rma.glmm() works correctly when using 'clogit' or 'clogistic'. ('test_misc_rma_glmm.r:89:4') - Reason: On CRAN
53. rma.glmm() works correctly for 'CM.EL' model. ('test_misc_rma_glmm.r:107:4') - Reason: On CRAN
54. rma.glmm() handles NAs correctly. ('test_misc_rma_handling_nas.r:9:4') - Reason: On CRAN
55. location-scale model works correctly for two subgroups with different tau^2 values ('test_misc_rma_ls.r:38:4') - Reason: On CRAN
56. profile() and confint() work correctly for location-scale models ('test_misc_rma_ls.r:49:4') - Reason: On CRAN
57. location-scale model works correctly for a continuous predictor ('test_misc_rma_ls.r:92:4') - Reason: On CRAN
58. location-scale model works correctly for multiple predictors ('test_misc_rma_ls.r:155:4') - Reason: On CRAN
59. permutation tests work correctly for a location-scale model ('test_misc_rma_ls.r:196:4') - Reason: On CRAN
60. predict() works correctly for location-scale models ('test_misc_rma_ls.r:218:4') - Reason: On CRAN
61. anova() works correctly for location-scale models ('test_misc_rma_ls.r:259:4') - Reason: On CRAN
62. vif() works correctly for location-scale models ('test_misc_rma_ls.r:296:4') - Reason: On CRAN
63. results are correct for a step function model. ('test_misc_selmodel.r:11:4') - Reason: On CRAN
64. results are correct for the beta function model. ('test_misc_selmodel.r:55:4') - Reason: On CRAN
65. results are correct for the various exponential function models. ('test_misc_selmodel.r:104:4') - Reason: On CRAN
66. results are correct for a pirori chosen step function models. ('test_misc_selmodel.r:162:4') - Reason: On CRAN
67. results are correct for a truncated distribution model. ('test_misc_selmodel.r:186:4') - Reason: On CRAN
68. .setlab() works correctly together with forest(). ('test_misc_setlab.r:14:4') - Reason: On CRAN
69. tes() works correctly for 'dat.dorn2007'. ('test_misc_tes.r:25:4') - Reason: On CRAN
70. update() works for rma.glmm(). ('test_misc_update.r:45:4') - Reason: On CRAN
71. plot can be drawn. ('test_plots_baujat_plot.r:13:4') - Reason: On CRAN
72. plot can be drawn. ('test_plots_caterpillar_plot.r:13:4') - Reason: On CRAN
73. plot can be drawn. ('test_plots_contour-enhanced_funnel_plot.r:13:4') - Reason: On CRAN
74. plot can be drawn for 'rma.uni' object. ('test_plots_cumulative_forest_plot.r:13:4') - Reason: On CRAN
75. plot can be drawn for 'rma.mh' object. ('test_plots_cumulative_forest_plot.r:44:4') - Reason: On CRAN
76. plot can be drawn for 'rma.peto' object. ('test_plots_cumulative_forest_plot.r:71:4') - Reason: On CRAN
77. plot can be drawn. ('test_plots_forest_plot_with_subgroups.r:13:4') - Reason: On CRAN
78. plot can be drawn. ('test_plots_funnel_plot_variations.r:13:4') - Reason: On CRAN
79. plot can be drawn. ('test_plots_funnel_plot_with_trim_and_fill.r:13:4') - Reason: On CRAN
80. plot can be drawn. ('test_plots_gosh.r:13:4') - Reason: On CRAN
81. plot can be drawn. ('test_plots_labbe_plot.r:13:4') - Reason: On CRAN
82. plot can be drawn. ('test_plots_llplot.r:11:4') - Reason: On CRAN
83. plot can be drawn. ('test_plots_meta-analytic_scatterplot.r:13:4') - Reason: On CRAN
84. plot can be drawn for 'rma.uni' object. ('test_plots_normal_qq_plots.r:13:4') - Reason: On CRAN
85. plot can be drawn for 'rma.mh' object. ('test_plots_normal_qq_plots.r:54:4') - Reason: On CRAN
86. plot can be drawn for 'rma.peto' object. ('test_plots_normal_qq_plots.r:72:4') - Reason: On CRAN
87. plot can be drawn. ('test_plots_plot_of_cumulative_results.r:13:4') - Reason: On CRAN
88. plot can be drawn. ('test_plots_plot_of_influence_diagnostics.r:13:4') - Reason: On CRAN
89. plot can be drawn. ('test_plots_radial_plot.r:13:4') - Reason: On CRAN
90. plot can be drawn. ('test_plots_regplot.r:13:4') - 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")`: Please install the 'lme4' package to fit this model.
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(...)
── 2. Error ('test_misc_rma_glmm.r:48:4'): 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 = "EE")`: Please install the 'lme4' package to fit this model.
Backtrace:
▆
1. ├─testthat::expect_warning(...) at test_misc_rma_glmm.r:48:4
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(...)
── 3. Error ('test_misc_rma_mv.r:102:4'): rma.mv() works correctly with differen
Error: Please install the 'minqa' package to use this optimizer.
Backtrace:
▆
1. └─metafor::rma.mv(...) at test_misc_rma_mv.r:102:4
2. └─metafor:::.chkopt(optimizer, optcontrol)
══ DONE ════════════════════════════════════════════════════════════════════════
Error: Test failures
Execution halted
Flavor: r-release-linux-x86_64
Version: 4.6-0
Check: HTML version of manual
Result: NOTE
Skipping checking math rendering: package 'V8' unavailable
Flavor: r-release-linux-x86_64
Version: 4.6-0
Check: installed package size
Result: NOTE
installed size is 5.2Mb
sub-directories of 1Mb or more:
R 2.1Mb
help 2.2Mb
Flavors: r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64