CRAN Package Check Results for Package ackwards

Last updated on 2026-08-03 14:50:34 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2.0 8.09 647.75 655.84 OK
r-devel-linux-x86_64-debian-gcc 0.2.0 5.53 410.77 416.30 NOTE
r-devel-linux-x86_64-fedora-clang 0.2.0 14.00 772.54 786.54 OK
r-devel-linux-x86_64-fedora-gcc 0.2.0 392.09 OK
r-devel-windows-x86_64 0.2.0 10.00 343.00 353.00 OK
r-patched-linux-x86_64 0.2.0 8.79 619.76 628.55 OK
r-release-linux-x86_64 0.2.0 6.61 634.25 640.86 OK
r-release-macos-arm64 0.2.0 2.00 83.00 85.00 OK
r-release-macos-x86_64 0.2.0 6.00 571.00 577.00 OK
r-release-windows-x86_64 0.2.0 9.00 344.00 353.00 OK
r-oldrel-macos-arm64 0.2.0 2.00 86.00 88.00 OK
r-oldrel-macos-x86_64 0.2.0 6.00 722.00 728.00 OK
r-oldrel-windows-x86_64 0.2.0 13.00 440.00 453.00 ERROR

Check Details

Version: 0.2.0
Check: for new files in some other directories
Result: NOTE Found the following files/directories: ‘~/tmp/scratch/Rtmp0KYl0s’ ‘~/tmp/scratch/Rtmp0UyhyU’ ‘~/tmp/scratch/Rtmp0ddwV6’ ‘~/tmp/scratch/Rtmp0pHy2C’ ‘~/tmp/scratch/Rtmp16688x’ ‘~/tmp/scratch/Rtmp17Ab63’ ‘~/tmp/scratch/Rtmp1F2nZn’ ‘~/tmp/scratch/Rtmp1Jnr5P’ ‘~/tmp/scratch/Rtmp1cDz3w’ ‘~/tmp/scratch/Rtmp1nbOQ8’ ‘~/tmp/scratch/Rtmp1xZVdu’ ‘~/tmp/scratch/Rtmp4I069J’ ‘~/tmp/scratch/Rtmp4hvMJJ’ ‘~/tmp/scratch/Rtmp4tr8dp’ ‘~/tmp/scratch/Rtmp5OKbe0’ ‘~/tmp/scratch/Rtmp5aL8Le’ ‘~/tmp/scratch/Rtmp6Y71zq’ ‘~/tmp/scratch/Rtmp6sCXA2’ ‘~/tmp/scratch/Rtmp7z2YG5’ ‘~/tmp/scratch/Rtmp8928Zz’ ‘~/tmp/scratch/Rtmp8PR2HX’ ‘~/tmp/scratch/Rtmp8Syv2g’ ‘~/tmp/scratch/Rtmp90EquT’ ‘~/tmp/scratch/Rtmp9E3BZa’ ‘~/tmp/scratch/RtmpA7qkIG’ ‘~/tmp/scratch/RtmpBJFD7o’ ‘~/tmp/scratch/RtmpBhHwIB’ ‘~/tmp/scratch/RtmpCGXFT3’ ‘~/tmp/scratch/RtmpClM9J5’ ‘~/tmp/scratch/RtmpD5PlW2’ ‘~/tmp/scratch/RtmpDJOSPN’ ‘~/tmp/scratch/RtmpDbUzAv’ ‘~/tmp/scratch/RtmpDrSqlV’ ‘~/tmp/scratch/RtmpDvRcI5’ ‘~/tmp/scratch/RtmpF8uHYw’ ‘~/tmp/scratch/RtmpGd4fB3’ ‘~/tmp/scratch/RtmpGrdwGM’ ‘~/tmp/scratch/RtmpHT4XML’ ‘~/tmp/scratch/RtmpHi4cHv’ ‘~/tmp/scratch/RtmpHmeoBD’ ‘~/tmp/scratch/RtmpHyPAK7’ ‘~/tmp/scratch/RtmpIIQGsV’ ‘~/tmp/scratch/RtmpIbk4qz’ ‘~/tmp/scratch/RtmpInHF3U’ ‘~/tmp/scratch/RtmpJGWBq7’ ‘~/tmp/scratch/RtmpJQZBWu’ ‘~/tmp/scratch/RtmpJmGTun’ ‘~/tmp/scratch/RtmpJnmgHy’ ‘~/tmp/scratch/RtmpKWNOPs’ ‘~/tmp/scratch/RtmpKwDyeB’ ‘~/tmp/scratch/RtmpLE1v8W’ ‘~/tmp/scratch/RtmpLMVtgH’ ‘~/tmp/scratch/RtmpLSRpdy’ ‘~/tmp/scratch/RtmpLWfEhr’ ‘~/tmp/scratch/RtmpLaCFJb’ ‘~/tmp/scratch/RtmpLhfdNX’ ‘~/tmp/scratch/RtmpMjn717’ ‘~/tmp/scratch/RtmpMohTUG’ ‘~/tmp/scratch/RtmpMvUT2H’ ‘~/tmp/scratch/RtmpND0ad4’ ‘~/tmp/scratch/RtmpNdy1Sc’ ‘~/tmp/scratch/RtmpNgM42I’ ‘~/tmp/scratch/RtmpO7OMga’ ‘~/tmp/scratch/RtmpOztBsH’ ‘~/tmp/scratch/RtmpQUu2YS’ ‘~/tmp/scratch/RtmpQvOdu2’ ‘~/tmp/scratch/RtmpR8b18H’ ‘~/tmp/scratch/RtmpRDHaGS’ ‘~/tmp/scratch/RtmpRTri8v’ ‘~/tmp/scratch/RtmpRbOW6f’ ‘~/tmp/scratch/RtmpRwIMtd’ ‘~/tmp/scratch/RtmpS3leyC’ ‘~/tmp/scratch/RtmpS9KZfw’ ‘~/tmp/scratch/RtmpSY4ZhA’ ‘~/tmp/scratch/RtmpSrbjia’ ‘~/tmp/scratch/RtmpTg8eH9’ ‘~/tmp/scratch/RtmpTtArlz’ ‘~/tmp/scratch/RtmpW3FWeP’ ‘~/tmp/scratch/RtmpWHSzHe’ ‘~/tmp/scratch/RtmpWNqA7h’ ‘~/tmp/scratch/RtmpWhv1fo’ ‘~/tmp/scratch/RtmpWzAjgt’ ‘~/tmp/scratch/RtmpX9O0aZ’ ‘~/tmp/scratch/RtmpXILYgZ’ ‘~/tmp/scratch/RtmpXrRQkt’ ‘~/tmp/scratch/RtmpY5og7L’ ‘~/tmp/scratch/RtmpY8NIYK’ ‘~/tmp/scratch/RtmpY8aRHf’ ‘~/tmp/scratch/RtmpZ0mpL1’ ‘~/tmp/scratch/RtmpZ3fYDD’ ‘~/tmp/scratch/RtmpZCm2SH’ ‘~/tmp/scratch/RtmpZXzLT0’ ‘~/tmp/scratch/RtmpZZN7NK’ ‘~/tmp/scratch/RtmpZgXfIn’ ‘~/tmp/scratch/RtmpaRcfZv’ ‘~/tmp/scratch/RtmpaZjktv’ ‘~/tmp/scratch/RtmpahaG35’ ‘~/tmp/scratch/RtmpaqUe0i’ ‘~/tmp/scratch/RtmpbB4dus’ ‘~/tmp/scratch/RtmpbRaWMo’ ‘~/tmp/scratch/Rtmpc8E8qk’ ‘~/tmp/scratch/RtmpcnWgqa’ ‘~/tmp/scratch/Rtmpd0l4A4’ ‘~/tmp/scratch/RtmpfNcirr’ ‘~/tmp/scratch/RtmpfTWOAG’ ‘~/tmp/scratch/RtmpftC4ke’ ‘~/tmp/scratch/Rtmpggkwvf’ ‘~/tmp/scratch/RtmpglB45w’ ‘~/tmp/scratch/RtmphBUt9o’ ‘~/tmp/scratch/RtmphFtxhe’ ‘~/tmp/scratch/RtmphebtP4’ ‘~/tmp/scratch/RtmpiFBEK1’ ‘~/tmp/scratch/RtmpiLV8vD’ ‘~/tmp/scratch/RtmpiZ4CUP’ ‘~/tmp/scratch/RtmpjSc1lc’ ‘~/tmp/scratch/RtmpjchBJl’ ‘~/tmp/scratch/RtmpkkLDO3’ ‘~/tmp/scratch/Rtmpl7KUZy’ ‘~/tmp/scratch/RtmplRCdUc’ ‘~/tmp/scratch/RtmpmHb4xX’ ‘~/tmp/scratch/RtmpmKnGF4’ ‘~/tmp/scratch/Rtmpmf5JCE’ ‘~/tmp/scratch/Rtmpmo199P’ ‘~/tmp/scratch/RtmpmoZHlh’ ‘~/tmp/scratch/RtmpnDSISb’ ‘~/tmp/scratch/RtmpnFX5Qh’ ‘~/tmp/scratch/RtmpnOFADu’ ‘~/tmp/scratch/RtmpnvZAlH’ ‘~/tmp/scratch/Rtmpo4T2F7’ ‘~/tmp/scratch/RtmpoKiyLV’ ‘~/tmp/scratch/RtmpoO3NOD’ ‘~/tmp/scratch/RtmppQB96J’ ‘~/tmp/scratch/RtmppYdhbb’ ‘~/tmp/scratch/RtmpphheoB’ ‘~/tmp/scratch/RtmppoYEuL’ ‘~/tmp/scratch/RtmpqFXdLB’ ‘~/tmp/scratch/RtmpqNos14’ ‘~/tmp/scratch/Rtmpqcrmag’ ‘~/tmp/scratch/RtmpqpO12y’ ‘~/tmp/scratch/Rtmpqsc4yQ’ ‘~/tmp/scratch/RtmprMcMGc’ ‘~/tmp/scratch/RtmpregpNn’ ‘~/tmp/scratch/RtmpreudT9’ ‘~/tmp/scratch/RtmprfsPQV’ ‘~/tmp/scratch/RtmpsLPYpt’ ‘~/tmp/scratch/RtmpsMoOSX’ ‘~/tmp/scratch/Rtmpsq2vMQ’ ‘~/tmp/scratch/RtmptxPj5h’ ‘~/tmp/scratch/RtmpuRjK4I’ ‘~/tmp/scratch/RtmpvSs6m0’ ‘~/tmp/scratch/RtmpvWUHyt’ ‘~/tmp/scratch/RtmpvaL6in’ ‘~/tmp/scratch/RtmpwSMrQo’ ‘~/tmp/scratch/RtmpwbiQjs’ ‘~/tmp/scratch/Rtmpwkzd73’ ‘~/tmp/scratch/RtmpwnUaMT’ ‘~/tmp/scratch/Rtmpxni4Hd’ ‘~/tmp/scratch/RtmpxuhqEA’ ‘~/tmp/scratch/Rtmpy3AiSU’ ‘~/tmp/scratch/Rtmpy7q1R3’ ‘~/tmp/scratch/RtmpyTUSV4’ ‘~/tmp/scratch/Rtmpyc02Vd’ ‘~/tmp/scratch/Rtmpz9jJPP’ ‘~/tmp/scratch/RtmpzhNcQj’ ‘~/tmp/scratch/xvfb-run.173FTf’ ‘~/tmp/scratch/xvfb-run.1FlpE5’ ‘~/tmp/scratch/xvfb-run.25U79P’ ‘~/tmp/scratch/xvfb-run.2Fiv1T’ ‘~/tmp/scratch/xvfb-run.2yLeaw’ ‘~/tmp/scratch/xvfb-run.4IuSUp’ ‘~/tmp/scratch/xvfb-run.5jQJDd’ ‘~/tmp/scratch/xvfb-run.6Fsnz6’ ‘~/tmp/scratch/xvfb-run.6NWrw1’ ‘~/tmp/scratch/xvfb-run.6hMDFC’ ‘~/tmp/scratch/xvfb-run.72cUIG’ ‘~/tmp/scratch/xvfb-run.749Y1u’ ‘~/tmp/scratch/xvfb-run.79OAPB’ ‘~/tmp/scratch/xvfb-run.7GaZxl’ ‘~/tmp/scratch/xvfb-run.7KxLxT’ ‘~/tmp/scratch/xvfb-run.82qN2g’ ‘~/tmp/scratch/xvfb-run.8iZn0A’ ‘~/tmp/scratch/xvfb-run.8tmbda’ ‘~/tmp/scratch/xvfb-run.9j3DLF’ ‘~/tmp/scratch/xvfb-run.AY4uMO’ ‘~/tmp/scratch/xvfb-run.AYKLOr’ ‘~/tmp/scratch/xvfb-run.AiNh7x’ ‘~/tmp/scratch/xvfb-run.BBHYNU’ ‘~/tmp/scratch/xvfb-run.Bq8CmW’ ‘~/tmp/scratch/xvfb-run.CVitdi’ ‘~/tmp/scratch/xvfb-run.DIha2H’ ‘~/tmp/scratch/xvfb-run.EEYzVK’ ‘~/tmp/scratch/xvfb-run.FxDCFd’ ‘~/tmp/scratch/xvfb-run.G9ihiK’ ‘~/tmp/scratch/xvfb-run.GW7rXD’ ‘~/tmp/scratch/xvfb-run.JBCjHL’ ‘~/tmp/scratch/xvfb-run.KlpirQ’ ‘~/tmp/scratch/xvfb-run.LUBPk0’ ‘~/tmp/scratch/xvfb-run.Lcd2DW’ ‘~/tmp/scratch/xvfb-run.LqvrXd’ ‘~/tmp/scratch/xvfb-run.NLFnwA’ ‘~/tmp/scratch/xvfb-run.NsZg61’ ‘~/tmp/scratch/xvfb-run.PKrd62’ ‘~/tmp/scratch/xvfb-run.Q2k47D’ ‘~/tmp/scratch/xvfb-run.QmgaiX’ ‘~/tmp/scratch/xvfb-run.RQEqOd’ ‘~/tmp/scratch/xvfb-run.RaCIWB’ ‘~/tmp/scratch/xvfb-run.Rt8eSP’ ‘~/tmp/scratch/xvfb-run.S76eaj’ ‘~/tmp/scratch/xvfb-run.W3QvnU’ ‘~/tmp/scratch/xvfb-run.XFrQmd’ ‘~/tmp/scratch/xvfb-run.Z8SM1V’ ‘~/tmp/scratch/xvfb-run.ZRchAp’ ‘~/tmp/scratch/xvfb-run.aEZLOX’ ‘~/tmp/scratch/xvfb-run.amoIOR’ ‘~/tmp/scratch/xvfb-run.cQWeUi’ ‘~/tmp/scratch/xvfb-run.cc57Ac’ ‘~/tmp/scratch/xvfb-run.dKJt4S’ ‘~/tmp/scratch/xvfb-run.eCVNEE’ ‘~/tmp/scratch/xvfb-run.eT6EZm’ ‘~/tmp/scratch/xvfb-run.ekGZf3’ ‘~/tmp/scratch/xvfb-run.g7gWg4’ ‘~/tmp/scratch/xvfb-run.gx34d9’ ‘~/tmp/scratch/xvfb-run.hXM9RJ’ ‘~/tmp/scratch/xvfb-run.hp3dp8’ ‘~/tmp/scratch/xvfb-run.i0ke7H’ ‘~/tmp/scratch/xvfb-run.jsfdxf’ ‘~/tmp/scratch/xvfb-run.jud1P5’ ‘~/tmp/scratch/xvfb-run.lWj2ij’ ‘~/tmp/scratch/xvfb-run.mT1Wh7’ ‘~/tmp/scratch/xvfb-run.mUkC11’ ‘~/tmp/scratch/xvfb-run.mWFYW1’ ‘~/tmp/scratch/xvfb-run.opnk2X’ ‘~/tmp/scratch/xvfb-run.rc1clt’ ‘~/tmp/scratch/xvfb-run.sDksQH’ ‘~/tmp/scratch/xvfb-run.uh7S5Z’ ‘~/tmp/scratch/xvfb-run.uorhAl’ ‘~/tmp/scratch/xvfb-run.vgssVj’ ‘~/tmp/scratch/xvfb-run.vmnP77’ ‘~/tmp/scratch/xvfb-run.xN6vMf’ ‘~/tmp/scratch/xvfb-run.yzUOK5’ ‘~/tmp/scratch/xvfb-run.zcDORd’ Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.2.0
Check: tests
Result: ERROR Running 'testthat.R' [195s] Running the tests in 'tests/testthat.R' failed. Complete output: > library(testthat) > library(ackwards) > > test_check("ackwards") Starting 2 test processes. > test-suggest_k.R: i Running parallel analysis (5 iterations, PC + FA)... > test-suggest_k.R: i PA-PC suggested 6 components -- above the evaluated ceiling (`k_max` = 3); reporting k <= 3. > test-suggest_k.R: i Increase `k_max` to evaluate the full suggestion. > test-suggest_k.R: i PA-FA suggested 6 factors -- above the evaluated ceiling (`k_max` = 3); reporting k <= 3. > test-suggest_k.R: i Increase `k_max` to evaluate the full suggestion. > test-suggest_k.R: v Running parallel analysis (5 iterations, PC + FA)... [546ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: CD: 364 rows with missing values removed (2436 complete cases used). > test-suggest_k.R: v Running MAP and VSS... [333ms] > test-suggest_k.R: > test-suggest_k.R: i Running Comparison Data (CD)... > test-suggest_k.R: v Running Comparison Data (CD)... [13s] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (5 iterations, PC + FA)... > test-suggest_k.R: v Running parallel analysis (5 iterations, PC + FA)... [190ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: CD: 54 rows with missing values removed (946 complete cases used). > test-suggest_k.R: v Running MAP and VSS... [133ms] > test-suggest_k.R: > test-suggest_k.R: i Running Comparison Data (CD)... > test-suggest_k.R: v Running Comparison Data (CD)... [2.8s] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (5 iterations, PC + FA)... > test-suggest_k.R: i PA-PC suggested 3 components -- above the evaluated ceiling (`k_max` = 2); reporting k <= 2. > test-suggest_k.R: i Increase `k_max` to evaluate the full suggestion. > test-suggest_k.R: i PA-FA suggested 5 factors -- above the evaluated ceiling (`k_max` = 2); reporting k <= 2. > test-suggest_k.R: i Increase `k_max` to evaluate the full suggestion. > test-suggest_k.R: v Running parallel analysis (5 iterations, PC + FA)... [356ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: CD: 86 rows with missing values removed (914 complete cases used). > test-suggest_k.R: v Running MAP and VSS... [144ms] > test-suggest_k.R: > test-suggest_k.R: i Running Comparison Data (CD)... > test-suggest_k.R: v Running Comparison Data (CD)... [3.5s] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (3 iterations, PC + FA)... > test-suggest_k.R: v Running parallel analysis (3 iterations, PC + FA)... [176ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: CD: 54 rows with missing values removed (946 complete cases used). > test-suggest_k.R: v Running MAP and VSS... [145ms] > test-suggest_k.R: > test-suggest_k.R: i Running Comparison Data (CD)... > test-suggest_k.R: v Running Comparison Data (CD)... [2s] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (3 iterations, PC + FA)... > test-suggest_k.R: v Running parallel analysis (3 iterations, PC + FA)... [147ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: CD: 54 rows with missing values removed (946 complete cases used). > test-suggest_k.R: v Running MAP and VSS... [157ms] > test-suggest_k.R: > test-suggest_k.R: i Running Comparison Data (CD)... > test-suggest_k.R: v Running Comparison Data (CD)... [1.9s] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: v Running MAP and VSS... [105ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: v Running MAP and VSS... [149ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: v Running MAP and VSS... [144ms] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (5 iterations, PC + FA)... > test-suggest_k.R: i PA-FA suggested 4 factors -- above the evaluated ceiling (`k_max` = 2); reporting k <= 2. > test-suggest_k.R: i Increase `k_max` to evaluate the full suggestion. > test-suggest_k.R: v Running parallel analysis (5 iterations, PC + FA)... [319ms] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (3 iterations, PC + FA)... > test-suggest_k.R: v Running parallel analysis (3 iterations, PC + FA)... [156ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: CD: 41 rows with missing values removed (959 complete cases used). > test-suggest_k.R: v Running MAP and VSS... [135ms] > test-suggest_k.R: > test-suggest_k.R: i Running Comparison Data (CD)... > test-suggest_k.R: v Running Comparison Data (CD)... [1.1s] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (3 iterations, PC + FA)... > test-suggest_k.R: v Running parallel analysis (3 iterations, PC + FA)... [149ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: i CD requires EFAtools (install to enable). > test-suggest_k.R: v Running MAP and VSS... [159ms] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (3 iterations, PC + FA)... > test-suggest_k.R: In smc, smcs < 0 were set to .0 > test-suggest_k.R: In smc, smcs < 0 were set to .0 > test-suggest_k.R: In smc, smcs < 0 were set to .0 > test-suggest_k.R: In factor.scores, the correlation matrix is singular, the pseudo inverse is used > test-suggest_k.R: In smc, smcs < 0 were set to .0 > test-suggest_k.R: In smc, smcs < 0 were set to .0 > test-suggest_k.R: In factor.scores, the correlation matrix is singular, the pseudo inverse is used > test-suggest_k.R: In smc, smcs < 0 were set to .0 > test-suggest_k.R: In smc, smcs < 0 were set to .0 > test-suggest_k.R: In factor.scores, the correlation matrix is singular, the pseudo inverse is used > test-suggest_k.R: In smc, smcs < 0 were set to .0 > test-suggest_k.R: In smc, smcs < 0 were set to .0 > test-suggest_k.R: In factor.scores, the correlation matrix is singular, the pseudo inverse is used > test-suggest_k.R: v Running parallel analysis (3 iterations, PC + FA)... [66ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: x Running MAP and VSS... [44ms] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (3 iterations, PC + FA)... > test-suggest_k.R: v Running parallel analysis (3 iterations, PC + FA)... [160ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: CD: 64 rows with missing values removed (936 complete cases used). > test-suggest_k.R: v Running MAP and VSS... [150ms] > test-suggest_k.R: > test-suggest_k.R: i Running Comparison Data (CD)... > test-suggest_k.R: v Running Comparison Data (CD)... [2.8s] > test-suggest_k.R: > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k PA-PC PA-FA MAP VSS-1 VSS-2 CD > test-suggest_k.R: 1 v v 0.0427* 0.6224 0.0000 v > test-suggest_k.R: 2 v v 0.0522 0.7305* 0.7981 v > test-suggest_k.R: 3 - v 0.0971 0.6415 0.8407 v* > test-suggest_k.R: 4 - - 0.1577 0.6451 0.8510* - > test-suggest_k.R: v retained * optimal k - not retained > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * PA-PC: k <= 2 > test-suggest_k.R: * PA-FA: k <= 3 > test-suggest_k.R: * MAP: k = 1 > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 4 > test-suggest_k.R: * CD: k = 3 > test-suggest_k.R: Consensus range: k = 1-4 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k PA-PC PA-FA MAP VSS-1 VSS-2 CD > test-suggest_k.R: 1 v v 0.0427* 0.6224 0.0000 v > test-suggest_k.R: 2 v v 0.0522 0.7305* 0.7981 v > test-suggest_k.R: 3 - v 0.0971 0.6415 0.8407 v* > test-suggest_k.R: 4 - - 0.1577 0.6451 0.8510* - > test-suggest_k.R: v retained * optimal k - not retained > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * PA-PC: k <= 2 > test-suggest_k.R: * PA-FA: k <= 3 > test-suggest_k.R: * MAP: k = 1 > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 4 > test-suggest_k.R: * CD: k = 3 > test-suggest_k.R: Consensus range: k = 1-4 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k PA-PC PA-FA MAP VSS-1 VSS-2 CD > test-suggest_k.R: 1 v - 0.0427* 0.6224 0.0000 v > test-suggest_k.R: 2 v - 0.0522 0.7305* 0.7981 v > test-suggest_k.R: 3 - - 0.0971 0.6415 0.8407 v* > test-suggest_k.R: 4 - - 0.1577 0.6451 0.8510* - > test-suggest_k.R: v retained * optimal k - not retained > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * PA-PC: k <= 2 > test-suggest_k.R: * PA-FA: undetermined (no FA factor exceeded random threshold) > test-suggest_k.R: * MAP: k = 1 > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 4 > test-suggest_k.R: * CD: k = 3 > test-suggest_k.R: Consensus range: k = 1-4 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k PA-PC PA-FA MAP VSS-1 VSS-2 CD > test-suggest_k.R: 1 v - 0.0427* 0.6224 0.0000 v > test-suggest_k.R: 2 v - 0.0522 0.7305* 0.7981 v > test-suggest_k.R: 3 - - 0.0971 0.6415 0.8407 v* > test-suggest_k.R: 4 - - 0.1577 0.6451 0.8510* - > test-suggest_k.R: v retained * optimal k - not retained > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * PA-PC: k <= 2 > test-suggest_k.R: * PA-FA: undetermined (no FA factor exceeded random threshold) > test-suggest_k.R: * MAP: k = 1 > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 4 > test-suggest_k.R: * CD: k = 3 > test-suggest_k.R: Consensus range: k = 1-4 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: i Running parallel analysis (20 iterations, PC + FA)... > test-suggest_k.R: v Running parallel analysis (20 iterations, PC + FA)... [1.1s] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: CD: 125 rows with missing values removed (875 complete cases used). > test-suggest_k.R: v Running MAP and VSS... [253ms] > test-suggest_k.R: > test-suggest_k.R: i Running Comparison Data (CD)... > test-suggest_k.R: v Running Comparison Data (CD)... [26.6s] > test-suggest_k.R: > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k PA-PC PA-FA MAP VSS-1 VSS-2 > test-suggest_k.R: 1 v v 0.0427* 0.6224 0.0000 > test-suggest_k.R: 2 v v 0.0522 0.7305* 0.7981 > test-suggest_k.R: 3 - v 0.0971 0.6415 0.8407 > test-suggest_k.R: 4 - - 0.1577 0.6451 0.8510* > test-suggest_k.R: v retained * optimal k - not retained > test-suggest_k.R: + CD requires EFAtools (install to enable). > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * PA-PC: k <= 2 > test-suggest_k.R: * PA-FA: k <= 3 > test-suggest_k.R: * MAP: k = 1 > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 4 > test-suggest_k.R: Consensus range: k = 1-4 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k PA-PC PA-FA MAP VSS-1 VSS-2 > test-suggest_k.R: 1 v v 0.0427* 0.6224 0.0000 > test-suggest_k.R: 2 v v 0.0522 0.7305* 0.7981 > test-suggest_k.R: 3 - v 0.0971 0.6415 0.8407 > test-suggest_k.R: 4 - - 0.1577 0.6451 0.8510* > test-suggest_k.R: v retained * optimal k - not retained > test-suggest_k.R: + CD requires EFAtools (install to enable). > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * PA-PC: k <= 2 > test-suggest_k.R: * PA-FA: k <= 3 > test-suggest_k.R: * MAP: k = 1 > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 4 > test-suggest_k.R: Consensus range: k = 1-4 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: i Running parallel analysis (3 iterations, PC + FA)... > test-suggest_k.R: i PA-FA suggested 3 factors -- above the evaluated ceiling (`k_max` = 2); reporting k <= 2. > test-suggest_k.R: i Increase `k_max` to evaluate the full suggestion. > test-suggest_k.R: v Running parallel analysis (3 iterations, PC + FA)... [219ms] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: CD: 41 rows with missing values removed (959 complete cases used). > test-suggest_k.R: v Running MAP and VSS... [162ms] > test-suggest_k.R: > test-suggest_k.R: i Running Comparison Data (CD)... > test-suggest_k.R: v Running Comparison Data (CD)... [751ms] > test-suggest_k.R: > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k PA-PC PA-FA MAP VSS-1 VSS-2 CD > test-suggest_k.R: 1 v v 0.0427* 0.6224 0.0000 v* > test-suggest_k.R: 2 v v 0.0522 0.7305* 0.7981 - > test-suggest_k.R: 3 - v 0.0971 0.6415 0.8407 - > test-suggest_k.R: 4 - - 0.1577 0.6451 0.8510* - > test-suggest_k.R: v retained * optimal k - not retained > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * PA-PC: k <= 2 > test-suggest_k.R: * PA-FA: k <= 3 > test-suggest_k.R: * MAP: k = 1 > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 4 > test-suggest_k.R: * CD: k = 1 > test-suggest_k.R: Consensus range: k = 1-4 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k PA-PC PA-FA MAP VSS-1 VSS-2 CD > test-suggest_k.R: 1 v v 0.0427* 0.6224 0.0000 v* > test-suggest_k.R: 2 v v 0.0522 0.7305* 0.7981 - > test-suggest_k.R: 3 - v 0.0971 0.6415 0.8407 - > test-suggest_k.R: 4 - - 0.1577 0.6451 0.8510* - > test-suggest_k.R: v retained * optimal k - not retained > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * PA-PC: k <= 2 > test-suggest_k.R: * PA-FA: k <= 3 > test-suggest_k.R: * MAP: k = 1 > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 4 > test-suggest_k.R: * CD: k = 1 > test-suggest_k.R: Consensus range: k = 1-4 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k PA-PC PA-FA MAP VSS-1 VSS-2 > test-suggest_k.R: 1 v v 0.0427 0.6224 0.0000 > test-suggest_k.R: 2 v v 0.0522* 0.7305* 0.7981* > test-suggest_k.R: 3 - v 0.0971 0.6415 0.8407 > test-suggest_k.R: 4 - - 0.1577 0.6451 0.8510 > test-suggest_k.R: v retained * optimal k - not retained > test-suggest_k.R: + CD requires EFAtools (install to enable). > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * PA-PC: k <= 2 > test-suggest_k.R: * PA-FA: k <= 2 > test-suggest_k.R: * MAP: k = 2 > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 2 > test-suggest_k.R: Consensus: k = 2 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k PA-PC PA-FA MAP VSS-1 VSS-2 > test-suggest_k.R: 1 v v 0.0427 0.6224 0.0000 > test-suggest_k.R: 2 v v 0.0522* 0.7305* 0.7981* > test-suggest_k.R: 3 - v 0.0971 0.6415 0.8407 > test-suggest_k.R: 4 - - 0.1577 0.6451 0.8510 > test-suggest_k.R: v retained * optimal k - not retained > test-suggest_k.R: + CD requires EFAtools (install to enable). > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * PA-PC: k <= 2 > test-suggest_k.R: * PA-FA: k <= 2 > test-suggest_k.R: * MAP: k = 2 > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 2 > test-suggest_k.R: Consensus: k = 2 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: v Running MAP and VSS... [59ms] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (5 iterations, PC + FA)... > test-suggest_k.R: v Running parallel analysis (5 iterations, PC + FA)... [191ms] > test-suggest_k.R: > test-suggest_k.R: CD: 54 rows with missing values removed (946 complete cases used). > test-suggest_k.R: i Running Comparison Data (CD)... > test-esem.R: > test-esem.R: -- Bass-Ackwards Analysis (ackwards) ------------------------------------------- > test-esem.R: Engine: esem > test-esem.R: Rotation: varimax > test-esem.R: Basis: pearson > test-esem.R: n: 200 > test-esem.R: k (max): 3 > test-esem.R: > test-esem.R: -- Levels -- > test-esem.R: > test-esem.R: v k = 1: 1 factor, 43.0% variance > test-esem.R: v k = 2: 2 factors, 85.2% variance > test-esem.R: v k = 3: 3 factors, 87.8% variance > test-esem.R: > test-esem.R: -- Edges -- > test-esem.R: > test-esem.R: 3 of 8 edges have |r| >= 0.3 > test-esem.R: -------------------------------------------------------------------------------- > test-esem.R: Note: This is a series of linked solutions, not a fitted hierarchical model. > test-esem.R: Cross-level edges are descriptive score correlations. Per-level fit indices > test-esem.R: (EFA/ESEM) describe how well a k-factor model fits the items at that level -- > test-esem.R: they do not validate the edges or the hierarchy itself. > test-suggest_k.R: v Running Comparison Data (CD)... [3.1s] > test-suggest_k.R: > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: v Running MAP and VSS... [74ms] > test-suggest_k.R: > test-suggest_k.R: > test-suggest_k.R: -- Factor / Component Count Suggestion (ackwards) ------------------------------ > test-suggest_k.R: Variables: 8 > test-suggest_k.R: n: 1,000 > test-suggest_k.R: Basis: pearson > test-suggest_k.R: Tested k: 1-4 > test-suggest_k.R: > test-suggest_k.R: -- Criteria (k = 1-4) -- > test-suggest_k.R: > test-suggest_k.R: k VSS-1 VSS-2 > test-suggest_k.R: 1 0.6224 0.0000 > test-suggest_k.R: 2 0.7305* 0.7981 > test-suggest_k.R: 3 0.6415 0.8407 > test-suggest_k.R: 4 0.6451 0.8510* > test-suggest_k.R: * optimal k > test-suggest_k.R: > test-suggest_k.R: -- Recommendations -- > test-suggest_k.R: > test-suggest_k.R: * VSS-1: k = 2 > test-suggest_k.R: * VSS-2: k = 4 > test-suggest_k.R: Consensus range: k = 2-4 > test-suggest_k.R: -------------------------------------------------------------------------------- > test-suggest_k.R: Note: k_max in ackwards() is a maximum depth. Setting k_max one or two levels > test-suggest_k.R: above the consensus to observe factor fragmentation is intentional. > test-suggest_k.R: Caution: PA-PC tends to overextract; structures may not replicate (Forbes, > test-suggest_k.R: 2023). PA-FA and CD are more conservative. Use the range. > test-suggest_k.R: i Running MAP and VSS... > test-suggest_k.R: v Running MAP and VSS... [70ms] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (3 iterations, PC + FA)... > test-suggest_k.R: v Running parallel analysis (3 iterations, PC + FA)... [111ms] > test-suggest_k.R: > test-suggest_k.R: i Running parallel analysis (3 iterations, PC + FA)... > test-suggest_k.R: v Running parallel analysis (3 iterations, PC + FA)... [149ms] > test-suggest_k.R: > test-layout.R: i Redundancy pruning (direct criterion, |r| >= 0.9) flagged 3 nodes. > test-layout.R: i Nodes are retained in the object; inspect with `x$prune$nodes` and `x$prune$chains`. > test-check-items.R: > test-check-items.R: -- Item quality check (ackwards) ----------------------------------------------- > test-check-items.R: Basis: pearson > test-check-items.R: Items: 5 > test-check-items.R: Flagged: 0 > test-check-items.R: v No item problems detected. > test-check-items.R: -------------------------------------------------------------------------------- > test-check-items.R: Constant items must be dropped (no variance). A near-constant item (one > test-check-items.R: response dominates) can yield a meaningless factor; a sparse category can make > test-check-items.R: `cor = "polychoric"` fail -- collapse rare categories, try `correct = 0`, or > test-check-items.R: drop the item. Full per-item table: treat this object as a data frame. > test-check-items.R: > test-check-items.R: -- Item quality check (ackwards) ----------------------------------------------- > test-check-items.R: Basis: polychoric > test-check-items.R: Items: 7 > test-check-items.R: Flagged: 2 > test-check-items.R: > test-check-items.R: -- Flagged items -- > test-check-items.R: > test-check-items.R: x constant: "const" > test-check-items.R: ! near-constant: "nc" > test-check-items.R: -------------------------------------------------------------------------------- > test-check-items.R: Constant items must be dropped (no variance). A near-constant item (one > test-check-items.R: response dominates) can yield a meaningless factor; a sparse category can make > test-check-items.R: `cor = "polychoric"` fail -- collapse rare categories, try `correct = 0`, or > test-check-items.R: drop the item. Full per-item table: treat this object as a data frame. > test-comparability.R: i Fitting 2 split-half replicates (pca, k = 1-3)... > test-comparability.R: v Fitting 2 split-half replicates (pca, k = 1-3)... [218ms] > test-comparability.R: > test-comparability.R: > test-comparability.R: -- Split-Half Factor Comparability (ackwards) ---------------------------------- > test-comparability.R: Engine: pca > test-comparability.R: Basis: pearson > test-comparability.R: n: 1,000 (500 per half) > test-comparability.R: Splits: 2 > test-comparability.R: Levels: 1-3 > test-comparability.R: > test-comparability.R: -- Comparability by level (median across splits) -- > test-comparability.R: > test-comparability.R: k = 1: median r 1.00, min r 1.00 (m1f1) > test-comparability.R: k = 2: median r 1.00, min r 1.00 (m2f2) > test-comparability.R: k = 3: median r .73, min r .28 (m3f2) [1/2 splits usable] > test-comparability.R: -------------------------------------------------------------------------------- > test-comparability.R: Per-factor detail (incl. Tucker's φ) in `$summary`; per-split values in > test-comparability.R: `$coefficients`. > test-comparability.R: Conventional benchmarks: >= .90 replication floor (Everett, 1983; Saucier et > test-comparability.R: al., 2005), >= .95 factors interchangeable (Lorenzo-Seva & ten Berge, 2006) -- > test-comparability.R: conventions, not tests. Interpret levels whose factors all replicate. > test-comparability.R: i Fitting 2 split-half replicates (pca, k = 1-3)... > test-comparability.R: v Fitting 2 split-half replicates (pca, k = 1-3)... [253ms] > test-comparability.R: > test-comparability.R: Error: ! testthat subprocess exited in file 'test-comparability.R'. Caused by error: ! R session crashed with exit code -1073741819 Backtrace: ▆ 1. └─testthat::test_check("ackwards") 2. └─testthat::test_dir(...) 3. └─testthat:::test_files(...) 4. └─testthat:::test_files_parallel(...) 5. ├─withr::with_dir(...) 6. │ └─base::force(code) 7. ├─testthat::with_reporter(...) 8. │ └─base::tryCatch(...) 9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers) 10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]]) 11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler) 12. └─testthat:::parallel_event_loop_chunky(queue, reporters, ".") 13. └─queue$poll(Inf) 14. └─base::lapply(...) 15. └─testthat (local) FUN(X[[i]], ...) 16. └─private$handle_error(msg, i) 17. └─cli::cli_abort(...) 18. └─rlang::abort(...) Execution halted Flavor: r-oldrel-windows-x86_64