NEWS.md
In ackwards: Bass-Ackwards Hierarchical Structural Analysis

ackwards 0.1.1

CRAN resubmission of the first release, addressing reviewer feedback on the 0.1.0 submission; also picks up everything added since that submission.

Fixed compatibility with lavaan 0.7. lavaan 0.7 renamed its sample-statistics slot argument (breaking the ESEM engine's multi-level reuse of anchor-level sample statistics — every level beyond k = 1 failed to build) and now requires an explicit ordered = FALSE to use WLSMV/ULSMV with continuous data. The ESEM engine detects the installed lavaan's argument vocabulary and works with both lavaan >= 0.7 and >= 0.6-13.
New vignette: "Reproducing Forbes (2023): The AMH Applied Example" (vignette("ackwards-forbes2023")). A full worked reproduction of the paper's 155-variable applied example on the bundled forbes2023 dataset: the 10-level hierarchy, skip-level correlations, the redundancy chase (including where the default direct criterion and the adjacent opt-in disagree), and the pruned-factor diagram in the paper's publication style.
Corrected the Forbes (2023) article title in the forbes2023 help page ("bass-ackward method", per the published title).
Corrected the n_obs advisory for PCA on correlation-matrix input. The message (and the n_obs help text) claimed supplying n_obs would enable chi-square/RMSEA/TLI, but the PCA engine's level fit is eigenvalue-based and never computes them; n_obs is recorded in the result metadata and feeds the N-based sampling-adequacy checks only. The message now says so. No behavior changes.
Completed the Goldberg (2006) reference to its full published title ("Doing it all Bass-Ackwards: The development of hierarchical factor structures from the top down") in the ackwards() help page and four vignettes.
Corrected the historical citations for comparability()'s split-half benchmarks. The .90 replication threshold traces to Everett (1983) and to its use in Goldberg's lexical research program by Saucier (1997) and Saucier, Georgiades, Tsaousis, and Goldberg (2005) — not to Goldberg (1990), which contains no split-half analyses and is no longer cited for this purpose. The .95 reference line is now sourced to Lorenzo-Seva and ten Berge (2006). Affects the roxygen help page, print()/autoplot() footer text, the README, and the replicability-workflow vignette; no behavior changes.
Sourced suggest_k()'s k-selection guidance. The consensus-range stance now cites Lim and Jahng (2019) with Achim's (2021) counterpoint, and the "PA-PC tends to overextract" note cites Saucier (1997) alongside Forbes (2023), in both the help page and the suggest-k vignette; no behavior changes.
label_template() now returns its scaffold visibly (behavior change). The named character vector carries class "ackwards_labels", and the editable c(...) literal is rendered by its print() method instead of being written to the console unconditionally. A top-level call looks the same as before; assigning the result (labs <- label_template(x)) or passing it inline (e.g. inside autoplot()) is now silent, per CRAN policy on console output.
DESCRIPTION now spells out principal component analysis (PCA), exploratory factor analysis (EFA), and exploratory structural equation modeling (ESEM) per CRAN feedback.
New bundled dataset forbes2023. The 155-variable "Assessing Mental Health" Spearman correlation matrix that forms Forbes's (2023) applied example is now exported, so ackwards(forbes2023, k_max = 10) reproduces her worked hierarchy directly. It joins bfi25 and sim16. The matrix is redistributed under CC-BY 4.0 with attribution to M. K. Forbes (see LICENSE.note).
prune("redundant") gains redundancy_criterion, defaulting to "direct" (behavior change). Redundancy chains are now traced by the direct (skip-level) correlation between a factor and each ancestor level — Forbes's (2023) actual ChaseCorrPaths rule — rather than the previous adjacent-hop walk. Because correlation is non-transitive, the two can differ in deep (many-level) hierarchies: on shallow ones (e.g. the bundled sim16) results are unchanged, but a factor can now be flagged redundant with an ancestor it correlates with directly even if an intermediate step is weak (and vice versa). Pass redundancy_criterion = "adjacent" for the old behavior. This makes prune("redundant") reproduce Forbes's published applied example exactly. print() and summary() name the active criterion. Note that under "direct", a chain's r_to_prev column reports the adjacent-level correlation and can sit below redundancy_r (membership is set by the direct skip-level link; see ?prune).
Validation. The Forbes (2023) fidelity suite now also reproduces her 155-variable "Assessing Mental Health" applied example (k_max = 10), not just the three simulation studies: between-level correlations match her reference implementation to 1.3e-14 across all 45 level-pairs, loading congruences agree within her two-decimal rounding, and her redundancy chase is reproduced for all 54 components. The published matrix ships as a test fixture under CC-BY 4.0 (see LICENSE.note).
suggest_k() now reads Comparison Data (CD) results from EFAtools >= 0.8.0, which restructured CD()'s return value (the per-iteration RMSE matrix moved from the top-level RMSE_eigenvalues field into results[[1]]$rmse_eigenvalues). Without this, the CD criterion and its autoplot() panel silently dropped out when a current EFAtools was installed. Older EFAtools versions still work.
Console output consistency. summary()'s per-level fit-index pass/fail mark is now the same terminal-adaptive cli glyph as print()'s convergence mark (a tick/cross that degrades to v/x in a non-UTF-8 console), replacing a hard-coded Unicode ✔/✘. And print()'s cumulative-variance percentages now carry a fixed single decimal (e.g. 20.0%, where a whole-number value previously printed as 20%), matching summary(). Cosmetic only; the reported values are unchanged.

ackwards 0.1.0

First public release. ackwards implements Goldberg's (2006) bass-ackwards method and its modern extensions: it fits factor solutions at every level from 1 to k and characterizes the hierarchy through the between-level factor-score correlations that connect them. Initial features, roughly in order of importance:

ackwards() — fit the hierarchy with a PCA, EFA, or ESEM engine; between-level edges from Waller's (2007) exact W′RW algebra.
suggest_k() — bracket a plausible depth range from five retention criteria (parallel analysis, MAP, VSS, Comparison Data).
comparability() — gate hierarchy depth on split-half replicability (Everett 1983; Goldberg 1990).
factorability() — screen a dataset (or correlation matrix) before you fit: Kaiser-Meyer-Olkin sampling adequacy (overall and per item), Bartlett's test of sphericity, the N:p ratio, and the Ledermann bound on identifiable factors, reported as numbers-and-bands rather than pass/fail. ackwards() runs a light version internally and warns only at the consequential extreme (k_max above the Ledermann bound for EFA/ESEM, or poor sampling adequacy).
Forbes (2023) extension — pairs = "all" skip-level edges, prune() for redundant/artifactual factors, and boot_edges() bootstrap edge CIs.
Ordinal data — cor = "polychoric" (WLSMV for ESEM), check_items() pre-analysis screening, and near-singularity diagnostics.
Interpretation & scoring — top_items() for reading factors; label_template()/set_factor_labels()/factor_labels() to attach persistent substantive names shown across print(), summary(), autoplot(), tidy(), and top_items(); augment()/predict() for factor scores, in and out of sample.
Output — autoplot() hierarchy diagrams and tidy()/glance()/summary().
Bundled data — bfi25 (ordinal Big Five) and sim16 (continuous), plus eight vignettes.