Last updated on 2025-12-05 13:51:16 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.3-0 | 4.74 | 75.36 | 80.10 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.3-0 | 3.23 | 46.57 | 49.80 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.3-0 | 11.00 | 114.42 | 125.42 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 1.3-0 | 119.16 | OK | |||
| r-devel-windows-x86_64 | 1.3-0 | 6.00 | 85.00 | 91.00 | OK | |
| r-patched-linux-x86_64 | 1.3-0 | 5.50 | 70.45 | 75.95 | OK | |
| r-release-linux-x86_64 | 1.3-0 | 4.03 | 72.31 | 76.34 | OK | |
| r-release-macos-arm64 | 1.3-0 | OK | ||||
| r-release-macos-x86_64 | 1.3-0 | 4.00 | 65.00 | 69.00 | OK | |
| r-release-windows-x86_64 | 1.3-0 | 6.00 | 86.00 | 92.00 | OK | |
| r-oldrel-macos-arm64 | 1.3-0 | OK | ||||
| r-oldrel-macos-x86_64 | 1.3-0 | 3.00 | 51.00 | 54.00 | OK | |
| r-oldrel-windows-x86_64 | 1.3-0 | 7.00 | 107.00 | 114.00 | OK |
Version: 1.3-0
Check: tests
Result: ERROR
Running ‘testthat.R’ [18s/18s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(ltmle)
>
> test_check("ltmle")
seed set to 1
Failed with error: 'there is no package called 'SuperLearner''
Saving _problems/test-CheckInputs-132.R
Failed with error: 'there is no package called 'SuperLearner''
Saving _problems/test-CheckInputs-133.R
Failed with error: 'there is no package called 'SuperLearner''
Saving _problems/test-CheckInputs-134.R
Estimator: tmle
Estimate Std. Error CI 2.5% CI 97.5% p-value
(Intercept) -3.5478 NA NA NA NA
time 0.5402 NA NA NA NA
switch.time NA NA NA NA NA
deterministic.g.function is inconsistent with data.
After setting Anodes to abar, the data looks like this:
W A1 A2 Y
1 1.6973939 0 1 1
2 1.0638812 0 1 1
3 -0.7666166 0 1 0
4 0.3820076 0 1 0
5 0.2418959 0 1 1
6 -1.1327594 0 1 1
Estimator: tmle
Call:
ltmle(data = data, Anodes = "A", Ynodes = "Y", abar = 1, gbounds = c(0,
1), estimate.time = FALSE)
Parameter Estimate: 0.60362
Estimated Std Err: 287.87
p-value: 0.99833
95% Conf Interval: (0, 1)
Error in solve.default(a) :
Lapack routine dgesv: system is exactly singular: U[2,2] = 0
Error in solve.default(a, b) :
Lapack routine dgesv: system is exactly singular: U[2,2] = 0
Call:
ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y",
abar = 1, estimate.time = F)
TMLE Estimate: 0.5891077
Estimator: tmle
Call:
ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y",
abar = 1, estimate.time = F)
Parameter Estimate: 0.58911
Estimated Std Err: 0.10025
p-value: 2.2363e-06
95% Conf Interval: (0.38408, 0.79414)
Call:
ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y",
abar = list(1, 0), estimate.time = F)
Use summary(...) to get estimates, standard errors, p-values, and confidence intervals for treatment EYd, control EYd, additive effect, relative risk, and odds ratio.
Estimator: tmle
Call:
ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y",
abar = list(1, 0), estimate.time = F)
Treatment Estimate:
Parameter Estimate: 0.58911
Estimated Std Err: 0.10025
p-value: 2.2363e-06
95% Conf Interval: (0.38408, 0.79414)
Control Estimate:
Parameter Estimate: 0.49873
Estimated Std Err: 0.19951
p-value: 0.018337
95% Conf Interval: (0.090676, 0.90678)
Additive Treatment Effect:
Parameter Estimate: 0.090378
Estimated Std Err: 0.22265
p-value: 0.68778
95% Conf Interval: (-0.36499, 0.54575)
Relative Risk:
Parameter Estimate: 1.1812
Est Std Err log(RR): 0.43379
p-value: 0.70384
95% Conf Interval: (0.48643, 2.8684)
Odds Ratio:
Parameter Estimate: 1.441
Est Std Err log(OR): 0.89643
p-value: 0.68658
95% Conf Interval: (0.23038, 9.0138)
Call:
ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y",
abar = 1, estimate.time = F)
TMLE Estimate: 0.5891077
Estimator: tmle
Call:
ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y",
abar = 1, estimate.time = F)
Parameter Estimate: 0.58911
Estimated Std Err: 0.10025
p-value: 2.2363e-06
95% Conf Interval: (0.38408, 0.79414)
Call:
ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y",
abar = list(1, 0), estimate.time = F)
Use summary(...) to get estimates, standard errors, p-values, and confidence intervals for treatment EYd, control EYd, additive effect, relative risk, and odds ratio.
Estimator: tmle
Call:
ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y",
abar = list(1, 0), estimate.time = F)
Treatment Estimate:
Parameter Estimate: 0.58911
Estimated Std Err: 0.10025
p-value: 2.2363e-06
95% Conf Interval: (0.38408, 0.79414)
Control Estimate:
Parameter Estimate: 0.49873
Estimated Std Err: 0.19951
p-value: 0.018337
95% Conf Interval: (0.090676, 0.90678)
Additive Treatment Effect:
Parameter Estimate: 0.090378
Estimated Std Err: 0.22265
p-value: 0.68778
95% Conf Interval: (-0.36499, 0.54575)
Relative Risk:
Parameter Estimate: 1.1812
Est Std Err log(RR): 0.43379
p-value: 0.70384
95% Conf Interval: (0.48643, 2.8684)
Odds Ratio:
Parameter Estimate: 1.441
Est Std Err log(OR): 0.89643
p-value: 0.68658
95% Conf Interval: (0.23038, 9.0138)
Call:
ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y",
abar = 1, estimate.time = F, gcomp = T)
GCOMP Estimate: 0.6098368
Estimator: gcomp
Warning: inference for gcomp is not accurate! It is based on TMLE influence curves.
Call:
ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y",
abar = 1, estimate.time = F, gcomp = T)
Parameter Estimate: 0.60984
Estimated Std Err: 0.10069
p-value: 1.3631e-06
95% Conf Interval: (0.40391, 0.81576)
[ FAIL 3 | WARN 153 | SKIP 6 | PASS 164 ]
══ Skipped tests (6) ═══════════════════════════════════════════════════════════
• On CRAN (4): 'test-(init).R:5:3', 'test-EstimateVariance.R:4:3',
'test-Weights.R:73:3', 'test-random.R:7:3'
• empty test (2): 'test-AbarAndRegimes.R:84:1', 'test-print.R:3:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test-CheckInputs.R:132:3'): cvControl requires correct names and makes a difference ──
`ltmle(...)` threw an error with unexpected message.
Expected match: "SL.cvControl must be a list"
Actual message: "SuperLearner package is required if SL.library is not NULL or 'glm'"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test-CheckInputs.R:132:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. └─ltmle::ltmle(...)
7. └─ltmle:::CreateInputs(...)
8. └─ltmle:::CheckInputs(...)
── Failure ('test-CheckInputs.R:133:3'): cvControl requires correct names and makes a difference ──
`ltmle(...)` threw an error with unexpected message.
Expected match: "The valid names for SL.cvControl are V, stratifyCV, shuffle. validRows is not currently supported."
Actual message: "SuperLearner package is required if SL.library is not NULL or 'glm'"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test-CheckInputs.R:133:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. └─ltmle::ltmle(...)
7. └─ltmle:::CreateInputs(...)
8. └─ltmle:::CheckInputs(...)
── Error ('test-CheckInputs.R:134:3'): cvControl requires correct names and makes a difference ──
Error in `CheckInputs(data, all.nodes, survivalOutcome, Qform, gform, gbounds, Yrange, deterministic.g.function, SL.library, SL.cvControl, regimes, working.msm, summary.measures, final.Ynodes, stratify, msm.weights, deterministic.Q.function, observation.weights, gcomp, variance.method, id)`: SuperLearner package is required if SL.library is not NULL or 'glm'
Backtrace:
▆
1. └─ltmle::ltmle(...) at test-CheckInputs.R:134:3
2. └─ltmle:::CreateInputs(...)
3. └─ltmle:::CheckInputs(...)
[ FAIL 3 | WARN 153 | SKIP 6 | PASS 164 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.3-0
Check: HTML version of manual
Result: NOTE
Skipping checking math rendering: package 'V8' unavailable
Flavor: r-devel-linux-x86_64-debian-gcc