CRAN Package Check Results for Package TrialEmulation

Last updated on 2025-02-23 15:50:00 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.0.4.0 40.83 601.48 642.31 OK
r-devel-linux-x86_64-debian-gcc 0.0.4.2 31.43 348.33 379.76 OK
r-devel-linux-x86_64-fedora-clang 0.0.4.2 978.28 OK
r-devel-linux-x86_64-fedora-gcc 0.0.4.2 971.65 OK
r-devel-macos-arm64 0.0.4.0 314.00 OK
r-devel-macos-x86_64 0.0.4.2 451.00 OK
r-devel-windows-x86_64 0.0.4.0 42.00 577.00 619.00 OK
r-patched-linux-x86_64 0.0.4.0 40.24 501.38 541.62 ERROR
r-release-linux-x86_64 0.0.4.2 38.49 520.77 559.26 OK
r-release-macos-arm64 0.0.4.0 257.00 OK
r-release-macos-x86_64 0.0.4.2 453.00 OK
r-release-windows-x86_64 0.0.4.0 48.00 585.00 633.00 OK
r-oldrel-macos-arm64 0.0.4.0 280.00 OK
r-oldrel-macos-x86_64 0.0.4.2 638.00 OK
r-oldrel-windows-x86_64 0.0.4.0 58.00 661.00 719.00 ERROR

Check Details

Version: 0.0.4.0
Check: tests
Result: ERROR Running ‘testthat.R’ [271s/343s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(TrialEmulation) > > data.table::setDTthreads(2) > test_check("TrialEmulation") Starting data manipulation Starting data extension Summary of extended data: Number of observations: 1939053 ------------------------------------------------------------ Starting data manipulation P(treatment = 1 | previous treatment = 0) for denominator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.84325 0.04785 -80.31 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 4329.7 on 21263 degrees of freedom Residual deviance: 4329.7 on 21263 degrees of freedom AIC: 4331.7 Number of Fisher Scoring iterations: 6 P(treatment = 1 | previous treatment = 0) for numerator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.84325 0.04785 -80.31 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 4329.7 on 21263 degrees of freedom Residual deviance: 4329.7 on 21263 degrees of freedom AIC: 4331.7 Number of Fisher Scoring iterations: 6 P(treatment = 1 | previous treatment = 1) for denominator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 4.37616 0.06815 64.21 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 2346.7 on 17555 degrees of freedom Residual deviance: 2346.7 on 17555 degrees of freedom AIC: 2348.7 Number of Fisher Scoring iterations: 7 P(treatment = 1 | previous treatment = 1) for numerator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 4.37616 0.06815 64.21 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 2346.7 on 17555 degrees of freedom Residual deviance: 2346.7 on 17555 degrees of freedom AIC: 2348.7 Number of Fisher Scoring iterations: 7 Starting data extension Summary of extended data: Number of observations: 963883 ------------------------------------------------------------ Starting data manipulation P(treatment = 1 | previous treatment = 0) for denominator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.32517 0.03599 -92.4 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 6948.7 on 23042 degrees of freedom Residual deviance: 6948.7 on 23042 degrees of freedom AIC: 6950.7 Number of Fisher Scoring iterations: 6 P(treatment = 1 | previous treatment = 0) for numerator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.32517 0.03599 -92.4 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 6948.7 on 23042 degrees of freedom Residual deviance: 6948.7 on 23042 degrees of freedom AIC: 6950.7 Number of Fisher Scoring iterations: 6 P(treatment = 1 | previous treatment = 1) for denominator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 3.9124 0.0453 86.37 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 4892.8 on 25356 degrees of freedom Residual deviance: 4892.8 on 25356 degrees of freedom AIC: 4894.8 Number of Fisher Scoring iterations: 6 P(treatment = 1 | previous treatment = 1) for numerator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 3.9124 0.0453 86.37 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 4892.8 on 25356 degrees of freedom Residual deviance: 4892.8 on 25356 degrees of freedom AIC: 4894.8 Number of Fisher Scoring iterations: 6 Starting data extension Summary of extended data: Number of observations: 1939053 ------------------------------------------------------------ Starting data manipulation P(treatment = 1 | previous treatment = 0) for denominator Call: glm(formula = treatment ~ age_s + x4 + x2 + x1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -0.13699 0.25792 -0.531 0.5953 age_s -0.04014 0.19890 -0.202 0.8401 x4 1.09583 0.21355 5.131 2.88e-07 *** x2 0.09687 0.19430 0.499 0.6181 x1 0.61385 0.36325 1.690 0.0911 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 232.27 on 169 degrees of freedom Residual deviance: 185.41 on 165 degrees of freedom AIC: 195.41 Number of Fisher Scoring iterations: 4 P(treatment = 1 | previous treatment = 0) for numerator Call: glm(formula = treatment ~ age_s + x4, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.12031 0.20308 0.592 0.554 age_s 0.01215 0.19512 0.062 0.950 x4 1.10863 0.21415 5.177 2.26e-07 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 232.27 on 169 degrees of freedom Residual deviance: 188.62 on 167 degrees of freedom AIC: 194.62 Number of Fisher Scoring iterations: 4 P(treatment = 1 | previous treatment = 1) for denominator Call: glm(formula = treatment ~ age_s + x4 + x2 + x1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.6783 0.2797 2.425 0.015318 * age_s -0.1924 0.2115 -0.910 0.362887 x4 0.8536 0.2218 3.849 0.000119 *** x2 0.3246 0.1963 1.653 0.098252 . x1 0.7923 0.4914 1.612 0.106867 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 188.83 on 150 degrees of freedom Residual deviance: 164.85 on 146 degrees of freedom AIC: 174.85 Number of Fisher Scoring iterations: 4 P(treatment = 1 | previous treatment = 1) for numerator Call: glm(formula = treatment ~ age_s + x4, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.7476 0.2520 2.967 0.003011 ** age_s -0.1686 0.2081 -0.810 0.417888 x4 0.7935 0.2163 3.669 0.000244 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 188.83 on 150 degrees of freedom Residual deviance: 170.78 on 148 degrees of freedom AIC: 176.78 Number of Fisher Scoring iterations: 4 Starting data extension Summary of extended data: Number of observations: 500 ------------------------------------------------------------ [ FAIL 10 | WARN 1 | SKIP 33 | PASS 429 ] ══ Skipped tests (33) ══════════════════════════════════════════════════════════ • On CRAN (33): 'test-data_utils.R:6:3', 'test-data_utils.R:111:3', 'test-data_utils.R:131:3', 'test-generics.R:25:3', 'test-generics.R:66:3', 'test-generics.R:95:3', 'test-modelling.R:99:3', 'test-modelling.R:154:3', 'test-modelling.R:175:3', 'test-modelling.R:205:3', 'test-modelling.R:229:3', 'test-modelling.R:266:3', 'test-modelling.R:290:3', 'test-modelling.R:314:3', 'test-modelling.R:357:3', 'test-modelling.R:431:3', 'test-predict.R:26:3', 'test-predict.R:51:3', 'test-predict.R:108:3', 'test-predict.R:171:3', 'test-sampling.R:5:3', 'test-sampling.R:15:3', 'test-sampling.R:34:3', 'test-sampling.R:54:3', 'test-sampling.R:86:3', 'test-sampling.R:103:3', 'test-sampling.R:180:3', 'test-te_weights.R:20:3', 'test-te_weights.R:62:3', 'test-trial_sequence.R:41:3', 'test-trial_sequence.R:45:3', 'test-trial_sequence.R:49:3', 'test-trial_sequence.R:56:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Failure ('test-te_datastore_duckdb.R:73:3'): sample_controls works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_01@outcome_data@data$id) (`actual`) not equal to c(...) (`expected`). `actual`: 7 9 14 15 21 21 29 32 and 32 more... `expected`: 1 10 13 14 15 21 27 29 32 ... ── Failure ('test-te_datastore_duckdb.R:83:3'): sample_controls works with trial_sequence objects containing te_datastore_duckdb objects ── sc_02@outcome_data@n_rows (`actual`) not equal to 756 (`expected`). `actual`: 761.0 `expected`: 756.0 ── Failure ('test-te_datastore_duckdb.R:101:3'): sample_controls works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_01@outcome_data@data$sample_weight) (`actual`) not equal to c(rep(1, 14), rep(100, 17)) (`expected`). `actual[29:33]`: 100 100 100 100 100 `expected[29:31]`: 100 100 100 ── Failure ('test-te_datastore_duckdb.R:102:3'): sample_controls works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_02@outcome_data@data$sample_weight) (`actual`) not equal to c(rep(1, 14), rep(2, 742)) (`expected`). `actual[754:761]`: 2 2 2 2 2 2 2 2 `expected[754:756]`: 2 2 2 ── Failure ('test-te_datastore_duckdb.R:112:3'): sample_controls works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_04@outcome_data@data$id) (`actual`) not equal to c(...) (`expected`). `actual`: 16.0 20.0 44.0 44.0 44.0 44.0 44.0 49.0 53.0 53.0 and 18 more... `expected`: 2.0 14.0 16.0 33.0 34.0 44.0 44.0 44.0 44.0 44.0 ... ── Failure ('test-te_datastore_duckdb.R:152:3'): load_expanded_data works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_01@outcome_data@data$id) (`actual`) not equal to c(...) (`expected`). `actual`: 7 9 14 15 21 21 29 32 and 32 more... `expected`: 1 10 13 14 15 21 27 29 32 ... ── Failure ('test-te_datastore_duckdb.R:162:3'): load_expanded_data works with trial_sequence objects containing te_datastore_duckdb objects ── sc_02@outcome_data@n_rows (`actual`) not equal to 756 (`expected`). `actual`: 761.0 `expected`: 756.0 ── Failure ('test-te_datastore_duckdb.R:182:3'): load_expanded_data works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_01@outcome_data@data$sample_weight) (`actual`) not equal to c(rep(1, 14), rep(100, 17)) (`expected`). `actual[29:33]`: 100 100 100 100 100 `expected[29:31]`: 100 100 100 ── Failure ('test-te_datastore_duckdb.R:183:3'): load_expanded_data works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_02@outcome_data@data$sample_weight) (`actual`) not equal to c(rep(1, 14), rep(2, 742)) (`expected`). `actual[754:761]`: 2 2 2 2 2 2 2 2 `expected[754:756]`: 2 2 2 ── Failure ('test-te_datastore_duckdb.R:193:3'): load_expanded_data works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_04@outcome_data@data$id) (`actual`) not equal to c(...) (`expected`). `actual`: 16.0 20.0 44.0 44.0 44.0 44.0 44.0 49.0 53.0 53.0 and 18 more... `expected`: 2.0 14.0 16.0 33.0 34.0 44.0 44.0 44.0 44.0 44.0 ... [ FAIL 10 | WARN 1 | SKIP 33 | PASS 429 ] Error: Test failures Execution halted Flavor: r-patched-linux-x86_64

Version: 0.0.4.0
Check: tests
Result: ERROR Running 'testthat.R' [335s] Running the tests in 'tests/testthat.R' failed. Complete output: > library(testthat) > library(TrialEmulation) > > data.table::setDTthreads(2) > test_check("TrialEmulation") Starting data manipulation Starting data extension Summary of extended data: Number of observations: 1939053 ------------------------------------------------------------ Starting data manipulation P(treatment = 1 | previous treatment = 0) for denominator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.84325 0.04785 -80.31 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 4329.7 on 21263 degrees of freedom Residual deviance: 4329.7 on 21263 degrees of freedom AIC: 4331.7 Number of Fisher Scoring iterations: 6 P(treatment = 1 | previous treatment = 0) for numerator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.84325 0.04785 -80.31 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 4329.7 on 21263 degrees of freedom Residual deviance: 4329.7 on 21263 degrees of freedom AIC: 4331.7 Number of Fisher Scoring iterations: 6 P(treatment = 1 | previous treatment = 1) for denominator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 4.37616 0.06815 64.21 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 2346.7 on 17555 degrees of freedom Residual deviance: 2346.7 on 17555 degrees of freedom AIC: 2348.7 Number of Fisher Scoring iterations: 7 P(treatment = 1 | previous treatment = 1) for numerator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 4.37616 0.06815 64.21 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 2346.7 on 17555 degrees of freedom Residual deviance: 2346.7 on 17555 degrees of freedom AIC: 2348.7 Number of Fisher Scoring iterations: 7 Starting data extension Summary of extended data: Number of observations: 963883 ------------------------------------------------------------ Starting data manipulation P(treatment = 1 | previous treatment = 0) for denominator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.32517 0.03599 -92.4 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 6948.7 on 23042 degrees of freedom Residual deviance: 6948.7 on 23042 degrees of freedom AIC: 6950.7 Number of Fisher Scoring iterations: 6 P(treatment = 1 | previous treatment = 0) for numerator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.32517 0.03599 -92.4 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 6948.7 on 23042 degrees of freedom Residual deviance: 6948.7 on 23042 degrees of freedom AIC: 6950.7 Number of Fisher Scoring iterations: 6 P(treatment = 1 | previous treatment = 1) for denominator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 3.9124 0.0453 86.37 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 4892.8 on 25356 degrees of freedom Residual deviance: 4892.8 on 25356 degrees of freedom AIC: 4894.8 Number of Fisher Scoring iterations: 6 P(treatment = 1 | previous treatment = 1) for numerator Call: glm(formula = treatment ~ 1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 3.9124 0.0453 86.37 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 4892.8 on 25356 degrees of freedom Residual deviance: 4892.8 on 25356 degrees of freedom AIC: 4894.8 Number of Fisher Scoring iterations: 6 Starting data extension Summary of extended data: Number of observations: 1939053 ------------------------------------------------------------ Starting data manipulation P(treatment = 1 | previous treatment = 0) for denominator Call: glm(formula = treatment ~ age_s + x4 + x2 + x1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -0.13699 0.25792 -0.531 0.5953 age_s -0.04014 0.19890 -0.202 0.8401 x4 1.09583 0.21355 5.131 2.88e-07 *** x2 0.09687 0.19430 0.499 0.6181 x1 0.61385 0.36325 1.690 0.0911 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 232.27 on 169 degrees of freedom Residual deviance: 185.41 on 165 degrees of freedom AIC: 195.41 Number of Fisher Scoring iterations: 4 P(treatment = 1 | previous treatment = 0) for numerator Call: glm(formula = treatment ~ age_s + x4, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.12031 0.20308 0.592 0.554 age_s 0.01215 0.19512 0.062 0.950 x4 1.10863 0.21415 5.177 2.26e-07 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 232.27 on 169 degrees of freedom Residual deviance: 188.62 on 167 degrees of freedom AIC: 194.62 Number of Fisher Scoring iterations: 4 P(treatment = 1 | previous treatment = 1) for denominator Call: glm(formula = treatment ~ age_s + x4 + x2 + x1, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.6783 0.2797 2.425 0.015318 * age_s -0.1924 0.2115 -0.910 0.362887 x4 0.8536 0.2218 3.849 0.000119 *** x2 0.3246 0.1963 1.653 0.098252 . x1 0.7923 0.4914 1.612 0.106867 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 188.83 on 150 degrees of freedom Residual deviance: 164.85 on 146 degrees of freedom AIC: 174.85 Number of Fisher Scoring iterations: 4 P(treatment = 1 | previous treatment = 1) for numerator Call: glm(formula = treatment ~ age_s + x4, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.7476 0.2520 2.967 0.003011 ** age_s -0.1686 0.2081 -0.810 0.417888 x4 0.7935 0.2163 3.669 0.000244 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 188.83 on 150 degrees of freedom Residual deviance: 170.78 on 148 degrees of freedom AIC: 176.78 Number of Fisher Scoring iterations: 4 Starting data extension Summary of extended data: Number of observations: 500 ------------------------------------------------------------ [ FAIL 10 | WARN 1 | SKIP 33 | PASS 429 ] ══ Skipped tests (33) ══════════════════════════════════════════════════════════ • On CRAN (33): 'test-data_utils.R:6:3', 'test-data_utils.R:111:3', 'test-data_utils.R:131:3', 'test-generics.R:25:3', 'test-generics.R:66:3', 'test-generics.R:95:3', 'test-modelling.R:99:3', 'test-modelling.R:154:3', 'test-modelling.R:175:3', 'test-modelling.R:205:3', 'test-modelling.R:229:3', 'test-modelling.R:266:3', 'test-modelling.R:290:3', 'test-modelling.R:314:3', 'test-modelling.R:357:3', 'test-modelling.R:431:3', 'test-predict.R:26:3', 'test-predict.R:51:3', 'test-predict.R:108:3', 'test-predict.R:171:3', 'test-sampling.R:5:3', 'test-sampling.R:15:3', 'test-sampling.R:34:3', 'test-sampling.R:54:3', 'test-sampling.R:86:3', 'test-sampling.R:103:3', 'test-sampling.R:180:3', 'test-te_weights.R:20:3', 'test-te_weights.R:62:3', 'test-trial_sequence.R:41:3', 'test-trial_sequence.R:45:3', 'test-trial_sequence.R:49:3', 'test-trial_sequence.R:56:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Failure ('test-te_datastore_duckdb.R:73:3'): sample_controls works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_01@outcome_data@data$id) (`actual`) not equal to c(...) (`expected`). `actual`: 7 9 14 15 21 21 29 32 and 32 more... `expected`: 1 10 13 14 15 21 27 29 32 ... ── Failure ('test-te_datastore_duckdb.R:83:3'): sample_controls works with trial_sequence objects containing te_datastore_duckdb objects ── sc_02@outcome_data@n_rows (`actual`) not equal to 756 (`expected`). `actual`: 761.0 `expected`: 756.0 ── Failure ('test-te_datastore_duckdb.R:101:3'): sample_controls works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_01@outcome_data@data$sample_weight) (`actual`) not equal to c(rep(1, 14), rep(100, 17)) (`expected`). `actual[29:33]`: 100 100 100 100 100 `expected[29:31]`: 100 100 100 ── Failure ('test-te_datastore_duckdb.R:102:3'): sample_controls works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_02@outcome_data@data$sample_weight) (`actual`) not equal to c(rep(1, 14), rep(2, 742)) (`expected`). `actual[754:761]`: 2 2 2 2 2 2 2 2 `expected[754:756]`: 2 2 2 ── Failure ('test-te_datastore_duckdb.R:112:3'): sample_controls works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_04@outcome_data@data$id) (`actual`) not equal to c(...) (`expected`). `actual`: 16.0 20.0 44.0 44.0 44.0 44.0 44.0 49.0 53.0 53.0 and 18 more... `expected`: 2.0 14.0 16.0 33.0 34.0 44.0 44.0 44.0 44.0 44.0 ... ── Failure ('test-te_datastore_duckdb.R:152:3'): load_expanded_data works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_01@outcome_data@data$id) (`actual`) not equal to c(...) (`expected`). `actual`: 7 9 14 15 21 21 29 32 and 32 more... `expected`: 1 10 13 14 15 21 27 29 32 ... ── Failure ('test-te_datastore_duckdb.R:162:3'): load_expanded_data works with trial_sequence objects containing te_datastore_duckdb objects ── sc_02@outcome_data@n_rows (`actual`) not equal to 756 (`expected`). `actual`: 761.0 `expected`: 756.0 ── Failure ('test-te_datastore_duckdb.R:182:3'): load_expanded_data works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_01@outcome_data@data$sample_weight) (`actual`) not equal to c(rep(1, 14), rep(100, 17)) (`expected`). `actual[29:33]`: 100 100 100 100 100 `expected[29:31]`: 100 100 100 ── Failure ('test-te_datastore_duckdb.R:183:3'): load_expanded_data works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_02@outcome_data@data$sample_weight) (`actual`) not equal to c(rep(1, 14), rep(2, 742)) (`expected`). `actual[754:761]`: 2 2 2 2 2 2 2 2 `expected[754:756]`: 2 2 2 ── Failure ('test-te_datastore_duckdb.R:193:3'): load_expanded_data works with trial_sequence objects containing te_datastore_duckdb objects ── sort(sc_04@outcome_data@data$id) (`actual`) not equal to c(...) (`expected`). `actual`: 16.0 20.0 44.0 44.0 44.0 44.0 44.0 49.0 53.0 53.0 and 18 more... `expected`: 2.0 14.0 16.0 33.0 34.0 44.0 44.0 44.0 44.0 44.0 ... [ FAIL 10 | WARN 1 | SKIP 33 | PASS 429 ] Error: Test failures Execution halted Flavor: r-oldrel-windows-x86_64

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.