CRAN Package Check Results for Package ComBatFamQC

Last updated on 2025-01-22 14:52:34 CET.

Flavor	Version	Tinstall	Tcheck	Ttotal	Status	Flags
r-devel-linux-x86_64-debian-gcc	1.0.2	11.59	192.73	204.32	OK
r-devel-linux-x86_64-fedora-clang	1.0.2			498.23	OK
r-devel-linux-x86_64-fedora-gcc	1.0.2			549.23	OK
r-devel-windows-x86_64	1.0.2	21.00	287.00	308.00	OK
r-patched-linux-x86_64	1.0.2	15.30	261.55	276.85	OK
r-release-macos-x86_64	1.0.2			184.00	ERROR
r-release-windows-x86_64	1.0.2	21.00	473.00	494.00	OK
r-oldrel-windows-x86_64	1.0.2	28.00	350.00	378.00	OK

Check Details

Version: 1.0.2
Check: tests
Result: ERROR Running ‘testthat.R’ [87s/85s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview > # * https://testthat.r-lib.org/articles/special-files.html > > library(testthat) > library(ComBatFamQC) > > test_check("ComBatFamQC") GAMLSS-RS iteration 1: Global Deviance = 11577.26 GAMLSS-RS iteration 2: Global Deviance = 11577.26 GAMLSS-RS iteration 3: Global Deviance = 11577.26 GAMLSS-RS iteration 1: Global Deviance = 11582.7 GAMLSS-RS iteration 2: Global Deviance = 11582.68 GAMLSS-RS iteration 3: Global Deviance = 11582.68 Starting data preparation for the batch effect diagnostic and harmonization stage... Taking the result from the visual preparation stage as input... No observation is dropped due to missing values. Starting Empirical Bayes assumption check... Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting Empirical Bayes assumption check... Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting first-time harmonization... Starting data preparation for the batch effect diagnostic and harmonization stage... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting first-time harmonization... fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient Starting data preparation for the batch effect diagnostic and harmonization stage... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting first-time harmonization... Starting data preparation for the batch effect diagnostic and harmonization stage... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting first-time harmonization... Starting data preparation for the batch effect diagnostic and harmonization stage... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting out-of-sample harmonization using the saved ComBat Model... Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting first-time harmonization... fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting first-time harmonization... fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: 1 level(s) are dropped, corresponding to 2 observations. Starting out-of-sample harmonization using the reference dataset... Joining with `by = join_by(ID, site, subid, IMAGE_ID, VISIT, visit, EXAM_DATE, dateAcquired, timedays, timeyrs, AGE, baselineAge, SEX, DIAGNOSIS, MMSCORE, manufac, manufac.model, manufac.model.site, manufac.model.strength.site, manufac.model.coil.site, manufac.model.coil.strength.site, manufac.model.strength.site.indicator, manufac.model.coil.strength.site.indicator, strength, Field_Strength, Manufacturer, Mfg_Model, Weighting, Pulse_Sequence, Slice_Thickness, TE, TR, TI, Coil, Flip_Angle, Acquisition_Plane, Matrix_X, Matrix_Y, Matrix_Z, Pixel_Spacing_X, Pixel_Spacing_Y, X, thickness.left.fusiform, thickness.left.inferior.parietal, thickness.left.inferior.temporal, thickness.left.isthmus.cingulate, thickness.left.lateral.occipital, thickness.left.lateral.orbitofrontal, thickness.left.lingual, thickness.left.medial.orbitofrontal, thickness.left.middle.temporal, thickness.left.parahippocampal, thickness.left.paracentral, thickness.left.pars.opercularis, thickness.left.pars.orbitalis, thickness.left.pars.triangularis, thickness.left.pericalcarine, thickness.left.postcentral, thickness.left.posterior.cingulate, thickness.left.precentral, thickness.left.precuneus, thickness.left.rostral.anterior.cingulate, thickness.left.rostral.middle.frontal, thickness.left.superior.frontal, thickness.left.superior.parietal, thickness.left.superior.temporal, thickness.left.supramarginal, thickness.left.transverse.temporal, thickness.left.insula, thickness.right.caudal.anterior.cingulate, thickness.right.caudal.middle.frontal, thickness.right.cuneus, thickness.right.entorhinal, thickness.right.fusiform, thickness.right.inferior.parietal, thickness.right.inferior.temporal, thickness.right.isthmus.cingulate, thickness.right.lateral.occipital, thickness.right.lateral.orbitofrontal, thickness.right.lingual, thickness.right.medial.orbitofrontal, thickness.right.middle.temporal, thickness.right.parahippocampal, thickness.right.paracentral, thickness.right.pars.opercularis, thickness.right.pars.orbitalis, thickness.right.pars.triangularis, thickness.right.pericalcarine, thickness.right.postcentral, thickness.right.posterior.cingulate, thickness.right.precentral, thickness.right.precuneus, thickness.right.rostral.anterior.cingulate, thickness.right.rostral.middle.frontal, thickness.right.superior.frontal, thickness.right.superior.parietal, thickness.right.superior.temporal, thickness.right.supramarginal, thickness.right.transverse.temporal, thickness.right.insula)` The reference data is included in the new unharmonized dataset Joining with `by = join_by(ID, site, subid, IMAGE_ID, VISIT, visit, EXAM_DATE, dateAcquired, timedays, timeyrs, AGE, baselineAge, SEX, DIAGNOSIS, MMSCORE, manufac, manufac.model, manufac.model.site, manufac.model.strength.site, manufac.model.coil.site, manufac.model.coil.strength.site, manufac.model.strength.site.indicator, manufac.model.coil.strength.site.indicator, strength, Field_Strength, Manufacturer, Mfg_Model, Weighting, Pulse_Sequence, Slice_Thickness, TE, TR, TI, Coil, Flip_Angle, Acquisition_Plane, Matrix_X, Matrix_Y, Matrix_Z, Pixel_Spacing_X, Pixel_Spacing_Y, X, thickness.left.fusiform, thickness.left.inferior.parietal, thickness.left.inferior.temporal, thickness.left.isthmus.cingulate, thickness.left.lateral.occipital, thickness.left.lateral.orbitofrontal, thickness.left.lingual, thickness.left.medial.orbitofrontal, thickness.left.middle.temporal, thickness.left.parahippocampal, thickness.left.paracentral, thickness.left.pars.opercularis, thickness.left.pars.orbitalis, thickness.left.pars.triangularis, thickness.left.pericalcarine, thickness.left.postcentral, thickness.left.posterior.cingulate, thickness.left.precentral, thickness.left.precuneus, thickness.left.rostral.anterior.cingulate, thickness.left.rostral.middle.frontal, thickness.left.superior.frontal, thickness.left.superior.parietal, thickness.left.superior.temporal, thickness.left.supramarginal, thickness.left.transverse.temporal, thickness.left.insula, thickness.right.caudal.anterior.cingulate, thickness.right.caudal.middle.frontal, thickness.right.cuneus, thickness.right.entorhinal, thickness.right.fusiform, thickness.right.inferior.parietal, thickness.right.inferior.temporal, thickness.right.isthmus.cingulate, thickness.right.lateral.occipital, thickness.right.lateral.orbitofrontal, thickness.right.lingual, thickness.right.medial.orbitofrontal, thickness.right.middle.temporal, thickness.right.parahippocampal, thickness.right.paracentral, thickness.right.pars.opercularis, thickness.right.pars.orbitalis, thickness.right.pars.triangularis, thickness.right.pericalcarine, thickness.right.postcentral, thickness.right.posterior.cingulate, thickness.right.precentral, thickness.right.precuneus, thickness.right.rostral.anterior.cingulate, thickness.right.rostral.middle.frontal, thickness.right.superior.frontal, thickness.right.superior.parietal, thickness.right.superior.temporal, thickness.right.supramarginal, thickness.right.transverse.temporal, thickness.right.insula)` Joining with `by = join_by(ID, site, subid, IMAGE_ID, VISIT, visit, EXAM_DATE, dateAcquired, timedays, timeyrs, AGE, baselineAge, SEX, DIAGNOSIS, MMSCORE, manufac, manufac.model, manufac.model.site, manufac.model.strength.site, manufac.model.coil.site, manufac.model.coil.strength.site, manufac.model.strength.site.indicator, manufac.model.coil.strength.site.indicator, strength, Field_Strength, Manufacturer, Mfg_Model, Weighting, Pulse_Sequence, Slice_Thickness, TE, TR, TI, Coil, Flip_Angle, Acquisition_Plane, Matrix_X, Matrix_Y, Matrix_Z, Pixel_Spacing_X, Pixel_Spacing_Y, X, thickness.left.fusiform, thickness.left.inferior.parietal, thickness.left.inferior.temporal, thickness.left.isthmus.cingulate, thickness.left.lateral.occipital, thickness.left.lateral.orbitofrontal, thickness.left.lingual, thickness.left.medial.orbitofrontal, thickness.left.middle.temporal, thickness.left.parahippocampal, thickness.left.paracentral, thickness.left.pars.opercularis, thickness.left.pars.orbitalis, thickness.left.pars.triangularis, thickness.left.pericalcarine, thickness.left.postcentral, thickness.left.posterior.cingulate, thickness.left.precentral, thickness.left.precuneus, thickness.left.rostral.anterior.cingulate, thickness.left.rostral.middle.frontal, thickness.left.superior.frontal, thickness.left.superior.parietal, thickness.left.superior.temporal, thickness.left.supramarginal, thickness.left.transverse.temporal, thickness.left.insula, thickness.right.caudal.anterior.cingulate, thickness.right.caudal.middle.frontal, thickness.right.cuneus, thickness.right.entorhinal, thickness.right.fusiform, thickness.right.inferior.parietal, thickness.right.inferior.temporal, thickness.right.isthmus.cingulate, thickness.right.lateral.occipital, thickness.right.lateral.orbitofrontal, thickness.right.lingual, thickness.right.medial.orbitofrontal, thickness.right.middle.temporal, thickness.right.parahippocampal, thickness.right.paracentral, thickness.right.pars.opercularis, thickness.right.pars.orbitalis, thickness.right.pars.triangularis, thickness.right.pericalcarine, thickness.right.postcentral, thickness.right.posterior.cingulate, thickness.right.precentral, thickness.right.precuneus, thickness.right.rostral.anterior.cingulate, thickness.right.rostral.middle.frontal, thickness.right.superior.frontal, thickness.right.superior.parietal, thickness.right.superior.temporal, thickness.right.supramarginal, thickness.right.transverse.temporal, thickness.right.insula)` fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: 1 level(s) are dropped, corresponding to 2 observations. Starting out-of-sample harmonization using the reference dataset... Joining with `by = join_by(ID, site, subid, IMAGE_ID, VISIT, visit, EXAM_DATE, dateAcquired, timedays, timeyrs, AGE, baselineAge, SEX, DIAGNOSIS, MMSCORE, manufac, manufac.model, manufac.model.site, manufac.model.strength.site, manufac.model.coil.site, manufac.model.coil.strength.site, manufac.model.strength.site.indicator, manufac.model.coil.strength.site.indicator, strength, Field_Strength, Manufacturer, Mfg_Model, Weighting, Pulse_Sequence, Slice_Thickness, TE, TR, TI, Coil, Flip_Angle, Acquisition_Plane, Matrix_X, Matrix_Y, Matrix_Z, Pixel_Spacing_X, Pixel_Spacing_Y, X, thickness.left.fusiform, thickness.left.inferior.parietal, thickness.left.inferior.temporal, thickness.left.isthmus.cingulate, thickness.left.lateral.occipital, thickness.left.lateral.orbitofrontal, thickness.left.lingual, thickness.left.medial.orbitofrontal, thickness.left.middle.temporal, thickness.left.parahippocampal, thickness.left.paracentral, thickness.left.pars.opercularis, thickness.left.pars.orbitalis, thickness.left.pars.triangularis, thickness.left.pericalcarine, thickness.left.postcentral, thickness.left.posterior.cingulate, thickness.left.precentral, thickness.left.precuneus, thickness.left.rostral.anterior.cingulate, thickness.left.rostral.middle.frontal, thickness.left.superior.frontal, thickness.left.superior.parietal, thickness.left.superior.temporal, thickness.left.supramarginal, thickness.left.transverse.temporal, thickness.left.insula, thickness.right.caudal.anterior.cingulate, thickness.right.caudal.middle.frontal, thickness.right.cuneus, thickness.right.entorhinal, thickness.right.fusiform, thickness.right.inferior.parietal, thickness.right.inferior.temporal, thickness.right.isthmus.cingulate, thickness.right.lateral.occipital, thickness.right.lateral.orbitofrontal, thickness.right.lingual, thickness.right.medial.orbitofrontal, thickness.right.middle.temporal, thickness.right.parahippocampal, thickness.right.paracentral, thickness.right.pars.opercularis, thickness.right.pars.orbitalis, thickness.right.pars.triangularis, thickness.right.pericalcarine, thickness.right.postcentral, thickness.right.posterior.cingulate, thickness.right.precentral, thickness.right.precuneus, thickness.right.rostral.anterior.cingulate, thickness.right.rostral.middle.frontal, thickness.right.superior.frontal, thickness.right.superior.parietal, thickness.right.superior.temporal, thickness.right.supramarginal, thickness.right.transverse.temporal, thickness.right.insula)` The reference data is included in the new unharmonized dataset Joining with `by = join_by(ID, site, subid, IMAGE_ID, VISIT, visit, EXAM_DATE, dateAcquired, timedays, timeyrs, AGE, baselineAge, SEX, DIAGNOSIS, MMSCORE, manufac, manufac.model, manufac.model.site, manufac.model.strength.site, manufac.model.coil.site, manufac.model.coil.strength.site, manufac.model.strength.site.indicator, manufac.model.coil.strength.site.indicator, strength, Field_Strength, Manufacturer, Mfg_Model, Weighting, Pulse_Sequence, Slice_Thickness, TE, TR, TI, Coil, Flip_Angle, Acquisition_Plane, Matrix_X, Matrix_Y, Matrix_Z, Pixel_Spacing_X, Pixel_Spacing_Y, X, thickness.left.fusiform, thickness.left.inferior.parietal, thickness.left.inferior.temporal, thickness.left.isthmus.cingulate, thickness.left.lateral.occipital, thickness.left.lateral.orbitofrontal, thickness.left.lingual, thickness.left.medial.orbitofrontal, thickness.left.middle.temporal, thickness.left.parahippocampal, thickness.left.paracentral, thickness.left.pars.opercularis, thickness.left.pars.orbitalis, thickness.left.pars.triangularis, thickness.left.pericalcarine, thickness.left.postcentral, thickness.left.posterior.cingulate, thickness.left.precentral, thickness.left.precuneus, thickness.left.rostral.anterior.cingulate, thickness.left.rostral.middle.frontal, thickness.left.superior.frontal, thickness.left.superior.parietal, thickness.left.superior.temporal, thickness.left.supramarginal, thickness.left.transverse.temporal, thickness.left.insula, thickness.right.caudal.anterior.cingulate, thickness.right.caudal.middle.frontal, thickness.right.cuneus, thickness.right.entorhinal, thickness.right.fusiform, thickness.right.inferior.parietal, thickness.right.inferior.temporal, thickness.right.isthmus.cingulate, thickness.right.lateral.occipital, thickness.right.lateral.orbitofrontal, thickness.right.lingual, thickness.right.medial.orbitofrontal, thickness.right.middle.temporal, thickness.right.parahippocampal, thickness.right.paracentral, thickness.right.pars.opercularis, thickness.right.pars.orbitalis, thickness.right.pars.triangularis, thickness.right.pericalcarine, thickness.right.postcentral, thickness.right.posterior.cingulate, thickness.right.precentral, thickness.right.precuneus, thickness.right.rostral.anterior.cingulate, thickness.right.rostral.middle.frontal, thickness.right.superior.frontal, thickness.right.superior.parietal, thickness.right.superior.temporal, thickness.right.supramarginal, thickness.right.transverse.temporal, thickness.right.insula)` Joining with `by = join_by(ID, site, subid, IMAGE_ID, VISIT, visit, EXAM_DATE, dateAcquired, timedays, timeyrs, AGE, baselineAge, SEX, DIAGNOSIS, MMSCORE, manufac, manufac.model, manufac.model.site, manufac.model.strength.site, manufac.model.coil.site, manufac.model.coil.strength.site, manufac.model.strength.site.indicator, manufac.model.coil.strength.site.indicator, strength, Field_Strength, Manufacturer, Mfg_Model, Weighting, Pulse_Sequence, Slice_Thickness, TE, TR, TI, Coil, Flip_Angle, Acquisition_Plane, Matrix_X, Matrix_Y, Matrix_Z, Pixel_Spacing_X, Pixel_Spacing_Y, X, thickness.left.fusiform, thickness.left.inferior.parietal, thickness.left.inferior.temporal, thickness.left.isthmus.cingulate, thickness.left.lateral.occipital, thickness.left.lateral.orbitofrontal, thickness.left.lingual, thickness.left.medial.orbitofrontal, thickness.left.middle.temporal, thickness.left.parahippocampal, thickness.left.paracentral, thickness.left.pars.opercularis, thickness.left.pars.orbitalis, thickness.left.pars.triangularis, thickness.left.pericalcarine, thickness.left.postcentral, thickness.left.posterior.cingulate, thickness.left.precentral, thickness.left.precuneus, thickness.left.rostral.anterior.cingulate, thickness.left.rostral.middle.frontal, thickness.left.superior.frontal, thickness.left.superior.parietal, thickness.left.superior.temporal, thickness.left.supramarginal, thickness.left.transverse.temporal, thickness.left.insula, thickness.right.caudal.anterior.cingulate, thickness.right.caudal.middle.frontal, thickness.right.cuneus, thickness.right.entorhinal, thickness.right.fusiform, thickness.right.inferior.parietal, thickness.right.inferior.temporal, thickness.right.isthmus.cingulate, thickness.right.lateral.occipital, thickness.right.lateral.orbitofrontal, thickness.right.lingual, thickness.right.medial.orbitofrontal, thickness.right.middle.temporal, thickness.right.parahippocampal, thickness.right.paracentral, thickness.right.pars.opercularis, thickness.right.pars.orbitalis, thickness.right.pars.triangularis, thickness.right.pericalcarine, thickness.right.postcentral, thickness.right.posterior.cingulate, thickness.right.precentral, thickness.right.precuneus, thickness.right.rostral.anterior.cingulate, thickness.right.rostral.middle.frontal, thickness.right.superior.frontal, thickness.right.superior.parietal, thickness.right.superior.temporal, thickness.right.supramarginal, thickness.right.transverse.temporal, thickness.right.insula)` fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient fixed-effect model matrix is rank deficient so dropping 1 column / coefficient Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting data preparation for the batch effect diagnostic and harmonization stage... Taking the result from the visual preparation stage as input... No observation is dropped due to missing values. Starting data preparation for the post-harmonization stage... No existing model is provided. Fitting the regression model from scratch! No observation is dropped due to missing values. Starting data preparation for the post-harmonization stage... No existing model is provided. Fitting the regression model from scratch! No observation is dropped due to missing values. Starting data preparation for the post-harmonization stage... No existing model is provided. Fitting the regression model from scratch! No observation is dropped due to missing values. Starting data preparation for the post-harmonization stage... No observation is dropped due to missing values. Template moved to: /var/folders/2b/t0kwbtmn3p7brv2mvx39c9cr0000gn/T//RtmpFekScz/file130718c0a187/diagnosis_report.qmd Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Starting first-time harmonization... Starting data preparation for the post-harmonization stage... No existing model is provided. Fitting the regression model from scratch! No observation is dropped due to missing values. New names: * `residual_y` -> `residual_y...1` * `residual_y` -> `residual_y...2` * `residual_y` -> `residual_y...3` * `residual_y` -> `residual_y...4` Starting data preparation for the post-harmonization stage... No existing model is provided. Fitting the regression model from scratch! No observation is dropped due to missing values. New names: * `X3` -> `X3...1` * `X3` -> `X3...2` * `X3` -> `X3...3` * `X3` -> `X3...4` Starting data preparation for the post-harmonization stage... No observation is dropped due to missing values. Starting data preparation for the post-harmonization stage... No existing model is provided. Fitting the regression model from scratch! No observation is dropped due to missing values. New names: * `residual_y` -> `residual_y...1` * `residual_y` -> `residual_y...2` * `residual_y` -> `residual_y...3` * `residual_y` -> `residual_y...4` Starting data preparation for the post-harmonization stage... No observation is dropped due to missing values. Starting data preparation for the post-harmonization stage... No observation is dropped due to missing values. New names: * `residual_y` -> `residual_y...1` * `residual_y` -> `residual_y...2` * `residual_y` -> `residual_y...3` * `residual_y` -> `residual_y...4` Starting data preparation for the post-harmonization stage... No existing model is provided. Fitting the regression model from scratch! No observation is dropped due to missing values. New names: * `residual_y` -> `residual_y...1` * `residual_y` -> `residual_y...2` * `residual_y` -> `residual_y...3` * `residual_y` -> `residual_y...4` Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Statistic Numer.DF Pseudo.R2 Analytic.p.value (Omnibus) 0.0495 2 0.0472 < 1e-20 *** manufacs 0.0495 2 0.0472 < 1e-20 *** --- Signif. codes: 0 "***" 0.001 "**" 0.01 "*" 0.05 "." 0.1 " " 1Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Statistic Numer.DF Pseudo.R2 Analytic.p.value (Omnibus) 0.363 2 0.266 < 1e-20 *** manufacs 0.363 2 0.266 < 1e-20 *** --- Signif. codes: 0 "***" 0.001 "**" 0.01 "*" 0.05 "." 0.1 " " 1refitting model(s) with ML (instead of REML) refitting model(s) with ML (instead of REML) refitting model(s) with ML (instead of REML) refitting model(s) with ML (instead of REML) Starting data preparation for the batch effect diagnostic and harmonization stage... The result from the visual prepration stage is not provided! The required parameters should be specified... No observation is dropped due to missing values. Batch levels that contain less than 3 observations are dropped: no batch level is dropped. Statistic Numer.DF Pseudo.R2 Analytic.p.value (Omnibus) 0.0534 2 0.0507 < 1e-20 *** manufacs 0.0534 2 0.0507 < 1e-20 *** --- Signif. codes: 0 "***" 0.001 "**" 0.01 "*" 0.05 "." 0.1 " " 1[ FAIL 2 | WARN 98 | SKIP 1 | PASS 219 ] ══ Skipped tests (1) ═══════════════════════════════════════════════════════════ • On CRAN (1): 'test-age_shiny.R:22:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test-comfam_shiny.R:5:3'): Launch Shiny App without error ─────────── Error in `app_initialize(self, private, app_dir = app_dir, ..., load_timeout = load_timeout, timeout = timeout, wait = wait, expect_values_screenshot_args = expect_values_screenshot_args, screenshot_args = screenshot_args, check_names = check_names, name = name, variant = variant, view = view, height = height, width = width, seed = seed, clean_logs = clean_logs, shiny_args = shiny_args, render_args = render_args, options = options)`: Error starting shiny application: Loading required package: shiny Attaching package: ‘dplyr’ The following objects are masked from ‘package:stats’: filter, lag The following objects are masked from ‘package:base’: intersect, setdiff, setequal, union Attaching package: ‘rlang’ The following object is masked from ‘package:magrittr’: set_names Running application in test mode. Listening on http://127.0.0.1:8080 createTcpServer: address already in use Error in initialize(...) : Failed to create server i You can inspect the failed AppDriver object via `rlang::last_error()$app` i AppDriver logs: {shinytest2} R info 07:15:34.65 Start AppDriver initialization {shinytest2} R info 07:15:36.48 Starting Shiny app {shinytest2} R info 07:15:38.97 Error while initializing AppDriver: Error starting shiny application: Loading required package: shiny Attaching package: ‘dplyr’ The following objects are masked from ‘package:stats’: filter, lag The following objects are masked from ‘package:base’: intersect, setdiff, setequal, union Attaching package: ‘rlang’ The following object is masked from ‘package:magrittr’: set_names Running application in test mode. Listening on http://127.0.0.1:8080 createTcpServer: address already in use Error in initialize(...) : Failed to create server {shiny} R stderr ----------- Loading required package: shiny {shiny} R stderr ----------- {shiny} R stderr ----------- Attaching package: ‘dplyr’ {shiny} R stderr ----------- {shiny} R stderr ----------- The following objects are masked from ‘package:stats’: {shiny} R stderr ----------- {shiny} R stderr ----------- filter, lag {shiny} R stderr ----------- {shiny} R stderr ----------- The following objects are masked from ‘package:base’: {shiny} R stderr ----------- {shiny} R stderr ----------- intersect, setdiff, setequal, union {shiny} R stderr ----------- {shiny} R stderr ----------- {shiny} R stderr ----------- Attaching package: ‘rlang’ {shiny} R stderr ----------- {shiny} R stderr ----------- The following object is masked from ‘package:magrittr’: {shiny} R stderr ----------- {shiny} R stderr ----------- set_names {shiny} R stderr ----------- {shiny} R stderr ----------- Running application in test mode. {shiny} R stderr ----------- {shiny} R stderr ----------- Listening on http://127.0.0.1:8080 {shiny} R stderr ----------- createTcpServer: address already in use {shiny} R stderr ----------- Error in initialize(...) : Failed to create server Caused by error in `app_start_shiny()`: ! Error starting shiny application: Loading required package: shiny Attaching package: ‘dplyr’ The following objects are masked from ‘package:stats’: filter, lag The following objects are masked from ‘package:base’: intersect, setdiff, setequal, union Attaching package: ‘rlang’ The following object is masked from ‘package:magrittr’: set_names Running application in test mode. Listening on http://127.0.0.1:8080 createTcpServer: address already in use Error in initialize(...) : Failed to create server ── Error ('test-help_function.R:224:3'): Exporting diagnosis result works correctly ── Error in `find_quarto()`: Quarto command-line tools path not found! Please make sure you have installed and added Quarto to your PATH or set the QUARTO_PATH environment variable. Backtrace: ▆ 1. └─ComBatFamQC::diag_save(temp_dir, result, use_quarto = TRUE) at test-help_function.R:224:3 2. └─quarto::quarto_render(...) 3. └─quarto:::find_quarto() 4. └─cli::cli_abort(quarto_not_found_msg) 5. └─rlang::abort(...) [ FAIL 2 | WARN 98 | SKIP 1 | PASS 219 ] Error: Test failures Execution halted Flavor: r-release-macos-x86_64