Last updated on 2025-12-03 05:50:53 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| bayestestR | 13 | ||
| insight | 3 | 1 | 9 |
| modelbased | 13 | ||
| parameters | 2 | 11 | |
| performance | 1 | 1 | 11 |
Current CRAN status: OK: 13
Current CRAN status: ERROR: 3, NOTE: 1, OK: 9
Version: 1.4.3
Check: examples
Result: ERROR
Running examples in ‘insight-Ex.R’ failed
The error most likely occurred in:
> ### Name: is_converged
> ### Title: Convergence test for mixed effects models
> ### Aliases: is_converged
>
> ### ** Examples
>
> ## Don't show:
> if (require("lme4", quietly = TRUE)) withAutoprint({ # examplesIf
+ ## End(Don't show)
+ library(lme4)
+ data(cbpp)
+ set.seed(1)
+ cbpp$x <- rnorm(nrow(cbpp))
+ cbpp$x2 <- runif(nrow(cbpp))
+
+ model <- glmer(
+ cbind(incidence, size - incidence) ~ period + x + x2 + (1 + x | herd),
+ data = cbpp,
+ family = binomial()
+ )
+
+ is_converged(model)
+ ## Don't show:
+ }) # examplesIf
> library(lme4)
> data(cbpp)
> set.seed(1)
> cbpp$x <- rnorm(nrow(cbpp))
> cbpp$x2 <- runif(nrow(cbpp))
> model <- glmer(cbind(incidence, size - incidence) ~ period + x + x2 +
+ (1 + x | herd), data = cbpp, family = binomial())
boundary (singular) fit: see help('isSingular')
> is_converged(model)
Error in h(simpleError(msg, call)) :
error in evaluating the argument 'a' in selecting a method for function 'solve': object 'Hessian' not found
Calls: withAutoprint ... eval -> eval -> <Anonymous> -> .handleSimpleError -> h
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-release-windows-x86_64
Version: 1.4.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [529s/299s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(insight)
> test_check("insight")
Starting 2 test processes.
> test-find_transformation.R: boundary (singular) fit: see help('isSingular')
> test-gamlss.R: GAMLSS-RS iteration 1: Global Deviance = 365.2328
> test-gamlss.R: GAMLSS-RS iteration
> test-gamlss.R: 2: Global Deviance = 365.1292
> test-gamlss.R: GAMLSS-RS iteration 3: Global Deviance = 365.1269
> test-gamlss.R: GAMLSS-RS iteration
> test-gamlss.R: 4: Global Deviance = 365.1268
> test-gamlss.R: GAMLSS-RS iteration 1: Global Deviance = 5779.746
> test-gamlss.R: GAMLSS-RS iteration
> test-gamlss.R: 2: Global Deviance = 5779.746
> test-gamlss.R: GAMLSS-RS iteration
> test-gamlss.R: 1: Global Deviance = 703.1164
> test-gamlss.R: GAMLSS-RS iteration 2: Global Deviance = 703.1164
Saving _problems/test-gee-5.R
Saving _problems/test-geeglm-10.R
> test-get_model.R: Loading required namespace: GPArotation
> test-get_random.R: boundary (singular) fit: see help('isSingular')
Saving _problems/test-get_datagrid-1089.R
> test-glmmPQL.R: iteration 1
Saving _problems/test-htest-192.R
Saving _problems/test-is_converged-16.R
> test-mmrm.R: mmrm() registered as emmeans extension
> test-mmrm.R: mmrm() registered as car::Anova extension
> test-model_info.R: boundary (singular) fit: see help('isSingular')
> test-nestedLogit.R: list(work = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L,
> test-nestedLogit.R: 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> test-nestedLogit.R: 0L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L,
> test-nestedLogit.R: 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
> test-nestedLogit.R: 1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L,
> test-nestedLogit.R: 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L,
> test-nestedLogit.R: 1L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L
> test-nestedLogit.R: ), full = c(1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L,
> test-nestedLogit.R: 1L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L,
> test-nestedLogit.R: 0L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L))
> test-polr.R:
> test-polr.R: Re-fitting to get Hessian
> test-polr.R:
> test-polr.R:
> test-polr.R: Re-fitting to get Hessian
> test-polr.R:
Saving _problems/test-rq-6.R
Saving _problems/test-rqs-9.R
> test-survey_coxph.R: Stratified
> test-survey_coxph.R: Independent Sampling design (with replacement)
> test-survey_coxph.R: dpbc <- survey::svydesign(
> test-survey_coxph.R: id = ~1,
> test-survey_coxph.R: prob = ~randprob,
> test-survey_coxph.R: strata = ~edema,
> test-survey_coxph.R: data = subset(pbc, randomized)
> test-survey_coxph.R: )
> test-survey_coxph.R: Stratified Independent Sampling design (with replacement)
> test-survey_coxph.R: dpbc <- survey::svydesign(
> test-survey_coxph.R: id = ~1,
> test-survey_coxph.R: prob = ~randprob,
> test-survey_coxph.R: strata = ~edema,
> test-survey_coxph.R: data = subset(pbc, randomized)
> test-survey_coxph.R: )
> test-survey_coxph.R: Stratified Independent Sampling design (with replacement)
> test-survey_coxph.R: dpbc <- survey::svydesign(
> test-survey_coxph.R: id = ~1,
> test-survey_coxph.R: prob = ~randprob,
> test-survey_coxph.R: strata = ~edema,
> test-survey_coxph.R: data = subset(pbc, randomized)
> test-survey_coxph.R: )
[ FAIL 7 | WARN 12 | SKIP 96 | PASS 3398 ]
══ Skipped tests (96) ══════════════════════════════════════════════════════════
• On CRAN (89): 'test-GLMMadaptive.R:2:1', 'test-averaging.R:1:1',
'test-bias_correction.R:1:1', 'test-blmer.R:262:3', 'test-brms.R:1:1',
'test-brms_aterms.R:1:1', 'test-brms_gr_random_effects.R:1:1',
'test-brms_missing.R:1:1', 'test-brms_mm.R:1:1', 'test-brms_von_mises.R:1:1',
'test-betareg.R:197:5', 'test-clean_names.R:109:3',
'test-clean_parameters.R:1:1', 'test-coxme.R:1:1', 'test-clmm.R:170:3',
'test-cpglmm.R:152:3', 'test-display.R:1:1', 'test-display.R:15:1',
'test-export_table.R:3:1', 'test-export_table.R:7:1',
'test-export_table.R:134:3', 'test-export_table.R:164:3',
'test-export_table.R:193:1', 'test-export_table.R:278:1',
'test-export_table.R:296:3', 'test-export_table.R:328:3',
'test-export_table.R:385:1', 'test-export_table.R:406:3',
'test-export_table.R:470:3', 'test-find_smooth.R:39:3', 'test-fixest.R:2:1',
'test-format_table.R:2:1', 'test-format_table_ci.R:72:1', 'test-gam.R:2:1',
'test-find_random.R:43:3', 'test-get_data.R:507:1',
'test-get_loglikelihood.R:143:3', 'test-get_loglikelihood.R:223:3',
'test-get_predicted.R:2:1', 'test-get_priors.R:1:1',
'test-get_varcov.R:43:3', 'test-get_varcov.R:57:3',
'test-get_datagrid.R:1068:3', 'test-get_datagrid.R:1105:5',
'test-is_converged.R:32:1', 'test-iv_robust.R:120:3', 'test-lavaan.R:1:1',
'test-lcmm.R:1:1', 'test-lme.R:28:3', 'test-lme.R:212:3',
'test-glmmTMB.R:67:3', 'test-glmmTMB.R:767:3', 'test-glmmTMB.R:803:3',
'test-glmmTMB.R:1142:3', 'test-marginaleffects.R:1:1', 'test-mgcv.R:1:1',
'test-mipo.R:1:1', 'test-mlogit.R:1:1', 'test-model_info.R:106:3',
'test-modelbased.R:1:1', 'test-mvrstanarm.R:1:1', 'test-null_model.R:85:3',
'test-panelr-asym.R:165:3', 'test-panelr.R:295:3', 'test-phylolm.R:1:1',
'test-print_parameters.R:1:1', 'test-r2_nakagawa_bernoulli.R:1:1',
'test-r2_nakagawa_beta.R:1:1', 'test-r2_nakagawa_binomial.R:1:1',
'test-r2_nakagawa_gamma.R:1:1', 'test-r2_nakagawa_linear.R:1:1',
'test-r2_nakagawa_negbin.R:1:1', 'test-r2_nakagawa_negbin_zi.R:1:1',
'test-r2_nakagawa_ordered_beta.R:1:1', 'test-r2_nakagawa_poisson.R:1:1',
'test-r2_nakagawa_poisson_zi.R:1:1',
'test-r2_nakagawa_truncated_poisson.R:1:1', 'test-r2_nakagawa_tweedie.R:1:1',
'test-rlmer.R:276:3', 'test-rms.R:1:1', 'test-rqss.R:1:1',
'test-rstanarm.R:1:1', 'test-sdmTMB.R:1:1', 'test-selection.R:2:1',
'test-spatial.R:2:1', 'test-svylme.R:1:1', 'test-tidymodels.R:1:1',
'test-vgam.R:2:1', 'test-weightit.R:1:1'
• On Linux (3): 'test-BayesFactorBF.R:1:1', 'test-MCMCglmm.R:1:1',
'test-get_data.R:161:3'
• Package `logistf` is loaded and breaks `mmrm::mmrm()` (1): 'test-mmrm.R:4:1'
• works interactively (2): 'test-coxph-panel.R:34:3', 'test-coxph.R:38:3'
• {bigglm} is not installed (1): 'test-model_info.R:24:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-gee.R:5:3'): (code run outside of `test_that()`) ───────────────
Error in `is.data.frame(data)`: lazy-load database '/data/gannet/ripley/R/R-clang/library/datasets/data/Rdata.rdb' is corrupt
Backtrace:
▆
1. ├─stats::model.frame(formula = breaks ~ tension, id = wool, data = warpbreaks)
2. └─stats::model.frame.default(...)
3. └─base::is.data.frame(data)
── Error ('test-geeglm.R:4:1'): (code run outside of `test_that()`) ────────────
Error in `is.data.frame(data)`: lazy-load database '/data/gannet/ripley/R/R-clang/library/datasets/data/Rdata.rdb' is corrupt
Backtrace:
▆
1. ├─stats::model.frame(...)
2. └─stats::model.frame.default(...)
3. └─base::is.data.frame(data)
── Error ('test-get_datagrid.R:1083:3'): get_datagrid - '=' in factor levels ───
Error in `with(warpbreaks, factor(ifelse(breaks < 26, "under26", ifelse(breaks > 34, ">34", "26<=34")), levels = c("under26", "26<=34", ">34")))`: lazy-load database '/data/gannet/ripley/R/R-clang/library/datasets/data/Rdata.rdb' is corrupt
Backtrace:
▆
1. └─base::with(...) at test-get_datagrid.R:1083:3
── Error ('test-htest.R:185:1'): (code run outside of `test_that()`) ───────────
Error in `aggregate(warpbreaks$breaks, by = list(w = warpbreaks$wool, t = warpbreaks$tension), FUN = mean)`: lazy-load database '/data/gannet/ripley/R/R-clang/library/datasets/data/Rdata.rdb' is corrupt
Backtrace:
▆
1. └─stats::aggregate(...) at test-htest.R:185:1
── Error ('test-is_converged.R:16:3'): is_converged ────────────────────────────
Error in `h(simpleError(msg, call))`: error in evaluating the argument 'a' in selecting a method for function 'solve': object 'Hessian' not found
Backtrace:
▆
1. ├─testthat::expect_true(is_converged(model)) at test-is_converged.R:16:3
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. ├─insight::is_converged(model)
5. ├─insight:::is_converged.merMod(model)
6. │ ├─base::with(x@optinfo$derivs, Matrix::solve(Hessian, gradient))
7. │ ├─base::with.default(x@optinfo$derivs, Matrix::solve(Hessian, gradient))
8. │ │ └─base::eval(substitute(expr), data, enclos = parent.frame())
9. │ │ └─base::eval(substitute(expr), data, enclos = parent.frame())
10. │ └─Matrix::solve(Hessian, gradient)
11. └─base::.handleSimpleError(...)
12. └─base (local) h(simpleError(msg, call))
── Error ('test-rq.R:5:1'): (code run outside of `test_that()`) ────────────────
Error in `is.data.frame(data)`: lazy-load database '/data/gannet/ripley/R/R-clang/library/datasets/data/Rdata.rdb' is corrupt
Backtrace:
▆
1. ├─stats::model.frame(...)
2. └─stats::model.frame.default(...)
3. └─base::is.data.frame(data)
── Error ('test-rqs.R:5:1'): (code run outside of `test_that()`) ───────────────
Error in `is.data.frame(data)`: lazy-load database '/data/gannet/ripley/R/R-clang/library/datasets/data/Rdata.rdb' is corrupt
Backtrace:
▆
1. ├─stats::model.frame(...)
2. └─stats::model.frame.default(...)
3. └─base::is.data.frame(data)
[ FAIL 7 | WARN 12 | SKIP 96 | PASS 3398 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.4.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [537s/327s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(insight)
> test_check("insight")
Starting 2 test processes.
> test-find_transformation.R: boundary (singular) fit: see help('isSingular')
> test-gamlss.R: GAMLSS-RS iteration
> test-gamlss.R: 1: Global Deviance = 365.2328
> test-gamlss.R: GAMLSS-RS iteration 2: Global Deviance = 365.1292
> test-gamlss.R: GAMLSS-RS iteration 3: Global Deviance = 365.1269
> test-gamlss.R: GAMLSS-RS iteration 4: Global Deviance = 365.1268
> test-gamlss.R: GAMLSS-RS iteration
> test-gamlss.R: 1: Global Deviance = 5779.746
> test-gamlss.R: GAMLSS-RS iteration 2: Global Deviance = 5779.746
> test-gamlss.R: GAMLSS-RS iteration
> test-gamlss.R: 1: Global Deviance = 703.1164
> test-gamlss.R: GAMLSS-RS iteration 2: Global Deviance = 703.1164
> test-get_model.R: Loading required namespace: GPArotation
> test-get_random.R: boundary (singular) fit: see help('isSingular')
> test-glmmPQL.R: iteration 1
Saving _problems/test-is_converged-16.R
> test-mmrm.R: mmrm() registered as emmeans extension
> test-mmrm.R: mmrm() registered as car::Anova extension
> test-model_info.R: boundary (singular) fit: see help('isSingular')
> test-nestedLogit.R: list(work = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L,
> test-nestedLogit.R: 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> test-nestedLogit.R: 0L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L,
> test-nestedLogit.R: 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
> test-nestedLogit.R: 1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L,
> test-nestedLogit.R: 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L,
> test-nestedLogit.R: 1L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L
> test-nestedLogit.R: ), full = c(1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L,
> test-nestedLogit.R: 1L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L,
> test-nestedLogit.R: 0L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L))
> test-polr.R:
> test-polr.R: Re-fitting to get Hessian
> test-polr.R:
> test-polr.R:
> test-polr.R: Re-fitting to get Hessian
> test-polr.R:
> test-survey_coxph.R: Stratified Independent Sampling design (with replacement)
> test-survey_coxph.R: dpbc <- survey::svydesign(
> test-survey_coxph.R: id = ~1,
> test-survey_coxph.R: prob = ~randprob,
> test-survey_coxph.R: strata = ~edema,
> test-survey_coxph.R: data = subset(pbc, randomized)
> test-survey_coxph.R: )
> test-survey_coxph.R: Stratified Independent Sampling design (with replacement)
> test-survey_coxph.R: dpbc <- survey::svydesign(
> test-survey_coxph.R: id = ~1,
> test-survey_coxph.R: prob = ~randprob,
> test-survey_coxph.R: strata = ~edema,
> test-survey_coxph.R: data = subset(pbc, randomized)
> test-survey_coxph.R: )
> test-survey_coxph.R: Stratified Independent Sampling design (with replacement)
> test-survey_coxph.R: dpbc <- survey::svydesign(
> test-survey_coxph.R: id = ~1,
> test-survey_coxph.R: prob = ~randprob,
> test-survey_coxph.R: strata = ~edema,
> test-survey_coxph.R: data = subset(pbc, randomized)
> test-survey_coxph.R: )
[ FAIL 1 | WARN 5 | SKIP 96 | PASS 3512 ]
══ Skipped tests (96) ══════════════════════════════════════════════════════════
• On CRAN (89): 'test-GLMMadaptive.R:2:1', 'test-averaging.R:1:1',
'test-bias_correction.R:1:1', 'test-blmer.R:262:3', 'test-brms.R:1:1',
'test-brms_aterms.R:1:1', 'test-brms_gr_random_effects.R:1:1',
'test-brms_missing.R:1:1', 'test-brms_mm.R:1:1', 'test-brms_von_mises.R:1:1',
'test-betareg.R:197:5', 'test-clean_names.R:109:3',
'test-clean_parameters.R:1:1', 'test-coxme.R:1:1', 'test-clmm.R:170:3',
'test-cpglmm.R:152:3', 'test-display.R:1:1', 'test-display.R:15:1',
'test-export_table.R:3:1', 'test-export_table.R:7:1',
'test-export_table.R:134:3', 'test-export_table.R:164:3',
'test-export_table.R:193:1', 'test-export_table.R:278:1',
'test-export_table.R:296:3', 'test-export_table.R:328:3',
'test-export_table.R:385:1', 'test-export_table.R:406:3',
'test-export_table.R:470:3', 'test-find_random.R:43:3', 'test-fixest.R:2:1',
'test-format_table.R:2:1', 'test-format_table_ci.R:72:1', 'test-gam.R:2:1',
'test-find_smooth.R:39:3', 'test-get_data.R:507:1',
'test-get_loglikelihood.R:143:3', 'test-get_loglikelihood.R:223:3',
'test-get_predicted.R:2:1', 'test-get_priors.R:1:1',
'test-get_varcov.R:43:3', 'test-get_varcov.R:57:3',
'test-get_datagrid.R:1068:3', 'test-get_datagrid.R:1105:5',
'test-is_converged.R:32:1', 'test-iv_robust.R:120:3', 'test-lavaan.R:1:1',
'test-lcmm.R:1:1', 'test-lme.R:28:3', 'test-lme.R:212:3',
'test-glmmTMB.R:67:3', 'test-glmmTMB.R:767:3', 'test-glmmTMB.R:803:3',
'test-glmmTMB.R:1142:3', 'test-marginaleffects.R:1:1', 'test-mgcv.R:1:1',
'test-mipo.R:1:1', 'test-mlogit.R:1:1', 'test-model_info.R:106:3',
'test-modelbased.R:1:1', 'test-mvrstanarm.R:1:1', 'test-null_model.R:85:3',
'test-panelr-asym.R:165:3', 'test-panelr.R:295:3', 'test-phylolm.R:1:1',
'test-print_parameters.R:1:1', 'test-r2_nakagawa_bernoulli.R:1:1',
'test-r2_nakagawa_beta.R:1:1', 'test-r2_nakagawa_binomial.R:1:1',
'test-r2_nakagawa_gamma.R:1:1', 'test-r2_nakagawa_linear.R:1:1',
'test-r2_nakagawa_negbin.R:1:1', 'test-r2_nakagawa_negbin_zi.R:1:1',
'test-r2_nakagawa_ordered_beta.R:1:1', 'test-r2_nakagawa_poisson.R:1:1',
'test-r2_nakagawa_poisson_zi.R:1:1',
'test-r2_nakagawa_truncated_poisson.R:1:1', 'test-r2_nakagawa_tweedie.R:1:1',
'test-rlmer.R:276:3', 'test-rms.R:1:1', 'test-rqss.R:1:1',
'test-rstanarm.R:1:1', 'test-sdmTMB.R:1:1', 'test-selection.R:2:1',
'test-spatial.R:2:1', 'test-svylme.R:1:1', 'test-tidymodels.R:1:1',
'test-vgam.R:2:1', 'test-weightit.R:1:1'
• On Linux (3): 'test-BayesFactorBF.R:1:1', 'test-MCMCglmm.R:1:1',
'test-get_data.R:161:3'
• Package `logistf` is loaded and breaks `mmrm::mmrm()` (1): 'test-mmrm.R:4:1'
• works interactively (2): 'test-coxph-panel.R:34:3', 'test-coxph.R:38:3'
• {bigglm} is not installed (1): 'test-model_info.R:24:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-is_converged.R:16:3'): is_converged ────────────────────────────
Error in `h(simpleError(msg, call))`: error in evaluating the argument 'a' in selecting a method for function 'solve': object 'Hessian' not found
Backtrace:
▆
1. ├─testthat::expect_true(is_converged(model)) at test-is_converged.R:16:3
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. ├─insight::is_converged(model)
5. ├─insight:::is_converged.merMod(model)
6. │ ├─base::with(x@optinfo$derivs, Matrix::solve(Hessian, gradient))
7. │ ├─base::with.default(x@optinfo$derivs, Matrix::solve(Hessian, gradient))
8. │ │ └─base::eval(substitute(expr), data, enclos = parent.frame())
9. │ │ └─base::eval(substitute(expr), data, enclos = parent.frame())
10. │ └─Matrix::solve(Hessian, gradient)
11. └─base::.handleSimpleError(...)
12. └─base (local) h(simpleError(msg, call))
[ FAIL 1 | WARN 5 | SKIP 96 | PASS 3512 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.4.3
Check: tests
Result: ERROR
Running 'testthat.R' [168s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(insight)
> test_check("insight")
Starting 2 test processes.
> test-find_transformation.R: boundary (singular) fit: see help('isSingular')
> test-gamlss.R: GAMLSS-RS iteration 1: Global Deviance = 365.2328
> test-gamlss.R: GAMLSS-RS iteration 2: Global Deviance = 365.1292
> test-gamlss.R: GAMLSS-RS iteration 3: Global Deviance = 365.1269
> test-gamlss.R: GAMLSS-RS iteration 4: Global Deviance = 365.1268
> test-gamlss.R: GAMLSS-RS iteration 1: Global Deviance = 5779.746
> test-gamlss.R: GAMLSS-RS iteration 2: Global Deviance = 5779.746
> test-gamlss.R: GAMLSS-RS iteration 1: Global Deviance = 703.1164
> test-gamlss.R: GAMLSS-RS iteration 2: Global Deviance = 703.1164
> test-get_model.R: Loading required namespace: GPArotation
> test-get_random.R: boundary (singular) fit: see help('isSingular')
> test-glmmPQL.R: iteration 1
Saving _problems/test-is_converged-16.R
> test-mmrm.R: mmrm() registered as emmeans extension
> test-mmrm.R: mmrm() registered as car::Anova extension
> test-model_info.R: boundary (singular) fit: see help('isSingular')
> test-nestedLogit.R: list(work = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L,
> test-nestedLogit.R: 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> test-nestedLogit.R: 0L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L,
> test-nestedLogit.R: 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
> test-nestedLogit.R: 1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L,
> test-nestedLogit.R: 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L,
> test-nestedLogit.R: 1L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L
> test-nestedLogit.R: ), full = c(1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L,
> test-nestedLogit.R: 1L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L,
> test-nestedLogit.R: 0L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L))
> test-polr.R:
> test-polr.R: Re-fitting to get Hessian
> test-polr.R:
> test-polr.R:
> test-polr.R: Re-fitting to get Hessian
> test-polr.R:
> test-survey_coxph.R: Stratified Independent Sampling design (with replacement)
> test-survey_coxph.R: dpbc <- survey::svydesign(
> test-survey_coxph.R: id = ~1,
> test-survey_coxph.R: prob = ~randprob,
> test-survey_coxph.R: strata = ~edema,
> test-survey_coxph.R: data = subset(pbc, randomized)
> test-survey_coxph.R: )
> test-survey_coxph.R: Stratified Independent Sampling design (with replacement)
> test-survey_coxph.R: dpbc <- survey::svydesign(
> test-survey_coxph.R: id = ~1,
> test-survey_coxph.R: prob = ~randprob,
> test-survey_coxph.R: strata = ~edema,
> test-survey_coxph.R: data = subset(pbc, randomized)
> test-survey_coxph.R: )
> test-survey_coxph.R: Stratified Independent Sampling design (with replacement)
> test-survey_coxph.R: dpbc <- survey::svydesign(
> test-survey_coxph.R: id = ~1,
> test-survey_coxph.R: prob = ~randprob,
> test-survey_coxph.R: strata = ~edema,
> test-survey_coxph.R: data = subset(pbc, randomized)
> test-survey_coxph.R: )
[ FAIL 1 | WARN 4 | SKIP 93 | PASS 3611 ]
══ Skipped tests (93) ══════════════════════════════════════════════════════════
• On CRAN (89): 'test-GLMMadaptive.R:2:1', 'test-averaging.R:1:1',
'test-bias_correction.R:1:1', 'test-betareg.R:197:5', 'test-brms.R:1:1',
'test-brms_aterms.R:1:1', 'test-brms_gr_random_effects.R:1:1',
'test-brms_missing.R:1:1', 'test-blmer.R:262:3', 'test-brms_mm.R:1:1',
'test-brms_von_mises.R:1:1', 'test-clean_names.R:109:3',
'test-clean_parameters.R:1:1', 'test-coxme.R:1:1', 'test-cpglmm.R:152:3',
'test-clmm.R:170:3', 'test-display.R:1:1', 'test-display.R:15:1',
'test-export_table.R:3:1', 'test-export_table.R:7:1',
'test-export_table.R:134:3', 'test-export_table.R:164:3',
'test-export_table.R:193:1', 'test-export_table.R:278:1',
'test-export_table.R:296:3', 'test-export_table.R:328:3',
'test-export_table.R:385:1', 'test-export_table.R:406:3',
'test-export_table.R:470:3', 'test-find_smooth.R:39:3', 'test-fixest.R:2:1',
'test-find_random.R:43:3', 'test-format_table.R:2:1',
'test-format_table_ci.R:72:1', 'test-gam.R:2:1', 'test-get_data.R:507:1',
'test-get_loglikelihood.R:143:3', 'test-get_loglikelihood.R:223:3',
'test-get_predicted.R:2:1', 'test-get_priors.R:1:1',
'test-get_varcov.R:43:3', 'test-get_varcov.R:57:3',
'test-get_datagrid.R:1068:3', 'test-get_datagrid.R:1105:5',
'test-is_converged.R:32:1', 'test-iv_robust.R:120:3', 'test-lavaan.R:1:1',
'test-lcmm.R:1:1', 'test-lme.R:28:3', 'test-lme.R:212:3',
'test-glmmTMB.R:67:3', 'test-glmmTMB.R:767:3', 'test-glmmTMB.R:803:3',
'test-glmmTMB.R:1142:3', 'test-marginaleffects.R:1:1', 'test-mgcv.R:1:1',
'test-mipo.R:1:1', 'test-mlogit.R:1:1', 'test-model_info.R:106:3',
'test-modelbased.R:1:1', 'test-mvrstanarm.R:1:1', 'test-null_model.R:85:3',
'test-panelr-asym.R:165:3', 'test-panelr.R:295:3', 'test-phylolm.R:1:1',
'test-print_parameters.R:1:1', 'test-r2_nakagawa_bernoulli.R:1:1',
'test-r2_nakagawa_beta.R:1:1', 'test-r2_nakagawa_binomial.R:1:1',
'test-r2_nakagawa_gamma.R:1:1', 'test-r2_nakagawa_linear.R:1:1',
'test-r2_nakagawa_negbin.R:1:1', 'test-r2_nakagawa_negbin_zi.R:1:1',
'test-r2_nakagawa_ordered_beta.R:1:1', 'test-r2_nakagawa_poisson.R:1:1',
'test-r2_nakagawa_poisson_zi.R:1:1',
'test-r2_nakagawa_truncated_poisson.R:1:1', 'test-r2_nakagawa_tweedie.R:1:1',
'test-rlmer.R:276:3', 'test-rms.R:1:1', 'test-rqss.R:1:1',
'test-rstanarm.R:1:1', 'test-sdmTMB.R:1:1', 'test-selection.R:2:1',
'test-spatial.R:2:1', 'test-svylme.R:1:1', 'test-tidymodels.R:1:1',
'test-vgam.R:2:1', 'test-weightit.R:1:1'
• Package `logistf` is loaded and breaks `mmrm::mmrm()` (1): 'test-mmrm.R:4:1'
• works interactively (2): 'test-coxph-panel.R:34:3', 'test-coxph.R:38:3'
• {bigglm} is not installed (1): 'test-model_info.R:24:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-is_converged.R:16:3'): is_converged ────────────────────────────
Error in `h(simpleError(msg, call))`: error in evaluating the argument 'a' in selecting a method for function 'solve': object 'Hessian' not found
Backtrace:
▆
1. ├─testthat::expect_true(is_converged(model)) at test-is_converged.R:16:3
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. ├─insight::is_converged(model)
5. ├─insight:::is_converged.merMod(model)
6. │ ├─base::with(x@optinfo$derivs, Matrix::solve(Hessian, gradient))
7. │ ├─base::with.default(x@optinfo$derivs, Matrix::solve(Hessian, gradient))
8. │ │ └─base::eval(substitute(expr), data, enclos = parent.frame())
9. │ │ └─base::eval(substitute(expr), data, enclos = parent.frame())
10. │ └─Matrix::solve(Hessian, gradient)
11. └─base::.handleSimpleError(...)
12. └─base (local) h(simpleError(msg, call))
[ FAIL 1 | WARN 4 | SKIP 93 | PASS 3611 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-windows-x86_64
Version: 1.4.3
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: 'fungible'
Flavor: r-oldrel-windows-x86_64
Current CRAN status: OK: 13
Current CRAN status: NOTE: 2, OK: 11
Version: 0.28.3
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘M3C’
Flavor: r-oldrel-macos-arm64
Version: 0.28.3
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: 'EGAnet'
Flavor: r-oldrel-windows-x86_64
Current CRAN status: ERROR: 1, NOTE: 1, OK: 11
Version: 0.15.2
Check: Rd files
Result: NOTE
checkRd: (-1) check_predictions.Rd:74: height/width attributes should be in pixels
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.15.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [19s/11s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(performance)
>
> test_check("performance")
Starting 2 test processes.
> test-check_itemscale.R: Some of the values are negative. Maybe affected items need to be
> test-check_itemscale.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-check_itemscale.R: Some of the values are negative. Maybe affected items need to be
> test-check_itemscale.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-check_itemscale.R: Some of the values are negative. Maybe affected items need to be
> test-check_itemscale.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-check_itemscale.R: Some of the values are negative. Maybe affected items need to be
> test-check_itemscale.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-check_itemscale.R: Some of the values are negative. Maybe affected items need to be
> test-check_itemscale.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-check_itemscale.R: Some of the values are negative. Maybe affected items need to be
> test-check_itemscale.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-check_itemscale.R: Some of the values are negative. Maybe affected items need to be
> test-check_itemscale.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-check_itemscale.R: Some of the values are negative. Maybe affected items need to be
> test-check_itemscale.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-check_itemscale.R: Some of the values are negative. Maybe affected items need to be
> test-check_itemscale.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-check_itemscale.R: Some of the values are negative. Maybe affected items need to be
> test-check_itemscale.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-check_collinearity.R: NOTE: 2 fixed-effect singletons were removed (2 observations).
Saving _problems/test-check_collinearity-157.R
Saving _problems/test-check_collinearity-185.R
> test-check_overdispersion.R: Overdispersion detected.
> test-check_overdispersion.R: Underdispersion detected.
> test-check_outliers.R: No outliers were detected (p = 0.238).
> test-glmmPQL.R: iteration 1
> test-item_discrimination.R: Some of the values are negative. Maybe affected items need to be
> test-item_discrimination.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-item_discrimination.R: Some of the values are negative. Maybe affected items need to be
> test-item_discrimination.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-item_discrimination.R: Some of the values are negative. Maybe affected items need to be
> test-item_discrimination.R: reverse-coded, e.g. using `datawizard::reverse()`.
> test-performance_aic.R: Model was not fitted with REML, however, `estimator = "REML"`. Set
> test-performance_aic.R: `estimator = "ML"` to obtain identical results as from `AIC()`.
[ FAIL 2 | WARN 2 | SKIP 41 | PASS 443 ]
══ Skipped tests (41) ══════════════════════════════════════════════════════════
• On CRAN (36): 'test-bootstrapped_icc_ci.R:2:3',
'test-bootstrapped_icc_ci.R:44:3', 'test-binned_residuals.R:163:3',
'test-binned_residuals.R:190:3', 'test-check_convergence.R:1:1',
'test-check_dag.R:1:1', 'test-check_distribution.R:1:1',
'test-check_itemscale.R:1:1', 'test-check_itemscale.R:100:1',
'test-check_model.R:1:1', 'test-check_collinearity.R:193:1',
'test-check_collinearity.R:226:1', 'test-check_residuals.R:2:3',
'test-check_singularity.R:2:3', 'test-check_singularity.R:30:3',
'test-check_zeroinflation.R:73:3', 'test-check_zeroinflation.R:112:3',
'test-check_outliers.R:115:3', 'test-check_outliers.R:339:3',
'test-helpers.R:1:1', 'test-item_omega.R:1:1', 'test-item_omega.R:31:3',
'test-compare_performance.R:1:1', 'test-mclogit.R:56:1',
'test-model_performance.bayesian.R:1:1',
'test-model_performance.lavaan.R:1:1', 'test-model_performance.merMod.R:2:3',
'test-model_performance.merMod.R:37:3', 'test-model_performance.psych.R:1:1',
'test-model_performance.rma.R:36:1', 'test-performance_reliability.R:23:3',
'test-pkg-ivreg.R:1:1', 'test-r2_bayes.R:39:3', 'test-r2_nagelkerke.R:35:3',
'test-rmse.R:39:3', 'test-test_likelihoodratio.R:55:1'
• On Mac (4): 'test-check_predictions.R:1:1', 'test-icc.R:1:1',
'test-nestedLogit.R:1:1', 'test-r2_nakagawa.R:1:1'
• getRversion() > "4.4.0" is TRUE (1): 'test-check_outliers.R:300:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test-check_collinearity.R:157:3'): check_collinearity | afex ──────
Expected `expect_message(ccoW <- check_collinearity(aW))` to throw a warning.
── Failure ('test-check_collinearity.R:185:3'): check_collinearity | afex ──────
Expected `expect_message(ccoW <- check_collinearity(aW))` to throw a warning.
[ FAIL 2 | WARN 2 | SKIP 41 | PASS 443 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-macos-arm64