Last updated on 2026-09-24 02:52:11 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.2.0 | 5.89 | 652.42 | 658.31 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.2.0 | 4.89 | 421.42 | 426.31 | OK | |
| r-devel-linux-x86_64-fedora-clang | 0.2.0 | 427.00 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 0.2.0 | 419.21 | OK | |||
| r-devel-windows-x86_64 | 0.2.0 | 11.00 | 362.00 | 373.00 | OK | |
| r-patched-linux-x86_64 | 0.2.0 | 9.08 | 622.85 | 631.93 | OK | |
| r-release-linux-x86_64 | 0.2.0 | 7.43 | 643.19 | 650.62 | 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 | 266.00 | 275.00 | ERROR | |
| 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 | 12.00 | 482.00 | 494.00 | OK |
Version: 0.2.0
Check: tests
Result: ERROR
Running 'testthat.R' [142s]
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)... [363ms]
> 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... [189ms]
> test-suggest_k.R:
> test-suggest_k.R: i Running Comparison Data (CD)...
> test-suggest_k.R: v Running Comparison Data (CD)... [11.4s]
> 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)... [160ms]
> 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... [99ms]
> test-suggest_k.R:
> test-suggest_k.R: i Running Comparison Data (CD)...
> test-suggest_k.R: v Running Comparison Data (CD)... [2.4s]
> 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)... [247ms]
> 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... [87ms]
> test-suggest_k.R:
> test-suggest_k.R: i Running Comparison Data (CD)...
> test-suggest_k.R: v Running Comparison Data (CD)... [2.7s]
> 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)... [99ms]
> 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... [79ms]
> test-suggest_k.R:
> test-suggest_k.R: i Running Comparison Data (CD)...
> test-suggest_k.R: v Running Comparison Data (CD)... [1.6s]
> 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)... [93ms]
> 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... [121ms]
> test-suggest_k.R:
> test-suggest_k.R: i Running Comparison Data (CD)...
> test-suggest_k.R: v Running Comparison Data (CD)... [1.7s]
> test-suggest_k.R:
> test-suggest_k.R: i Running MAP and VSS...
> test-suggest_k.R: v Running MAP and VSS... [77ms]
> test-suggest_k.R:
> test-suggest_k.R: i Running MAP and VSS...
> test-suggest_k.R: v Running MAP and VSS... [84ms]
> test-suggest_k.R:
> test-suggest_k.R: i Running MAP and VSS...
> test-suggest_k.R: v Running MAP and VSS... [108ms]
> 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)... [244ms]
> 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)... [88ms]
> 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... [105ms]
> test-suggest_k.R:
> test-suggest_k.R: i Running Comparison Data (CD)...
> test-suggest_k.R: v Running Comparison Data (CD)... [738ms]
> 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)... [100ms]
> 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... [81ms]
> 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)... [54ms]
> 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)... [98ms]
> 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... [88ms]
> test-suggest_k.R:
> test-suggest_k.R: i Running Comparison Data (CD)...
> test-suggest_k.R: v Running Comparison Data (CD)... [2.4s]
> 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)... [715ms]
> 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... [171ms]
> test-suggest_k.R:
> 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)... [20.3s]
> 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)... [143ms]
> 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... [107ms]
> test-suggest_k.R:
> test-suggest_k.R: i Running Comparison Data (CD)...
> test-suggest_k.R: v Running Comparison Data (CD)... [685ms]
> 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... [35ms]
> 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)... [130ms]
> 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-suggest_k.R: v Running Comparison Data (CD)... [2.4s]
> test-suggest_k.R:
> test-suggest_k.R: i Running MAP and VSS...
> test-suggest_k.R: v Running MAP and VSS... [42ms]
> 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... [41ms]
> 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)... [90ms]
> 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)... [133ms]
> 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)... [156ms]
> 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)... [171ms]
> 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: no usable splits (half-solutions did not converge)
> 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:
> 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: 4
> test-comparability.R: Levels: 1-5
> 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 (m2f1)
> test-comparability.R: k = 3: median r .80, min r .58 (m3f2)
> test-comparability.R: k = 4: median r 1.00, min r 1.00 (m4f2)
> test-comparability.R: k = 5: median r .99, min r .14 (m5f5)
> 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:
> 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: 4
> test-comparability.R: Levels: 1-5
> 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 (m2f1)
> test-comparability.R: k = 3: median r .80, min r .58 (m3f2)
> test-comparability.R: k = 4: median r 1.00, min r 1.00 (m4f2)
> test-comparability.R: k = 5: median r .99, min r .14 (m5f5)
> 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:
> test-comparability.R: Likely variables with missing values are
> test-comparability.R: i6
> test-comparability.R:
> test-comparability.R: Likely variables with missing values are
> test-comparability.R: i6
> 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: 1-2 (requested 1-3; full-sample fit truncated)
> 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: --------------------------------------------------------------------------------
> 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-cor-input.R:
> test-cor-input.R: -- Bass-Ackwards Analysis (ackwards) -------------------------------------------
> test-cor-input.R: Engine: pca
> test-cor-input.R: Rotation: varimax
> test-cor-input.R: Basis: (user-supplied matrix)
> test-cor-input.R: n: NA
> test-cor-input.R: k (max): 3
> test-cor-input.R:
> test-cor-input.R: -- Levels --
> test-cor-input.R:
> test-cor-input.R: v k = 1: 1 factor, 41.8% variance
> test-cor-input.R: v k = 2: 2 factors, 58.5% variance
> test-cor-input.R: v k = 3: 3 factors, 72.2% variance
> test-cor-input.R:
> test-cor-input.R: -- Edges --
> test-cor-input.R:
> test-cor-input.R: 5 of 8 edges have |r| >= 0.3
> test-cor-input.R: --------------------------------------------------------------------------------
> test-cor-input.R: Note: This is a series of linked solutions, not a fitted hierarchical model.
> test-cor-input.R: Cross-level edges are descriptive score correlations. Per-level fit indices
> test-cor-input.R: (EFA/ESEM) describe how well a k-factor model fits the items at that level --
> test-cor-input.R: they do not validate the edges or the hierarchy itself.
> test-cor-input.R:
> test-cor-input.R: -- Bass-Ackwards Analysis (ackwards) -------------------------------------------
> test-cor-input.R: Engine: pca
> test-cor-input.R: Rotation: varimax
> test-cor-input.R: Basis: (user-supplied matrix)
> test-cor-input.R: n: NA
> test-cor-input.R: k (max): 3
> test-cor-input.R:
> test-cor-input.R: -- Levels --
> test-cor-input.R:
> test-cor-input.R: v k = 1: 1 factor, 41.8% variance
> test-cor-input.R: v k = 2: 2 factors, 58.5% variance
> test-cor-input.R: v k = 3: 3 factors, 72.2% variance
> test-cor-input.R:
> test-cor-input.R: -- Edges --
> test-cor-input.R:
> test-cor-input.R: 5 of 8 edges have |r| >= 0.3
> test-cor-input.R: --------------------------------------------------------------------------------
> test-cor-input.R: Note: This is a series of linked solutions, not a fitted hierarchical model.
> test-cor-input.R: Cross-level edges are descriptive score correlations. Per-level fit indices
> test-cor-input.R: (EFA/ESEM) describe how well a k-factor model fits the items at that level --
> test-cor-input.R: they do not validate the edges or the hierarchy itself.
> test-cor-input.R:
Error:
! testthat subprocess exited in file 'test-cor-input.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-release-windows-x86_64