bifactory 0.6.0

Fixes and additions prompted by the review of the Teacher’s Corner manuscript. The minor version is bumped because reported values change: SRMR now follows the Mplus definition, composite reliabilities use absolute loadings, and lavaan >= 0.7-2 is required. Point estimates and fit of the previously correct paths are unchanged. Prose now says “ordinal” instead of “ordered-categorical”; function and argument names (esem_ordered(), ordered = TRUE) are unchanged.

Dependencies

• lavaan >= 0.7-2 is required. From that version the polychoric correlations equal the exact two-step maximum-likelihood values, which multi-group comparisons with Mplus depend on.

Documentation

• Roxygen markdown is enabled, so the reference manual renders headings, bold text, bullet lists and tables. A test fails if raw markdown reaches the Rd files.

Multi-group reference group

• esem_invariance() passes the sorted group levels to lavaan as group.label, so the reference group is the first sorted level in R and in the Mplus syntax written by run_mplus_besem_invariance() alike. Loadings and factor covariances are therefore oriented to the same group in both programs.

Ordinal configural identification

• The ordinal configural model (ESEM and B-ESEM, theta parameterization) uses the standard identification in every group: residual variances 1, factor means 0, all thresholds free. Same df, equivalent model, faster convergence, and the generated Mplus syntax follows. Configural fit indices change by at most 0.001.

ESEM-within-CFA

• fit_ewc(var_fixed = FALSE) re-expresses the source ESEM exactly and is honoured for a B-ESEM source (referent primary loadings fixed, factor variances free, covariances 0).
• The ordinal plain EWC is refitted under the source ESEM’s parameterization, so freed factor variances read 1.00.
• The ordinal B-ESEM-within-CFA reports its own fit (df = B-ESEM df + k(k-1)/2); print() and compare_ewc() agree with each other and with Mplus.

Reporting under MLR

• print() of ESEM, B-ESEM and EWC fits, fit_indices(), compare_ewc(), the parameters() header and esem_compare() report the robust chi-square, CFI, TLI and RMSEA, matching the comparison table.
• esem_compare() fits its CFA with the ESEM’s estimator, robust test, standard errors, missing-data setting and, for ordinal items, parameterization, so both columns are like for like.

Fit indices

• SRMR is computed as Mplus defines it (Asparouhov & Muthén, 2018) for every lavaan-based fit: correlation, variance and standardized-mean residuals for continuous items (denominator p(p+1)/2 + p), polychoric and category-probability residuals for ordinal items (denominator p(p-1)/2 + total categories), pooled over groups by sample size. Multi-group values agree with Mplus to three decimals at every invariance level of the validation runs; single-group values are unchanged at three decimals. The custom DWLS B-ESEM path uses the same denominator.

Reliability

• compute_indices() sums absolute standardized loadings in every composite (Morin, Arens & Marsh, 2016), so reverse-scoring an item or reflecting a factor changes nothing (test-reliability.R). For CFA and ESEM the residual variance comes from the model-implied item variance (one minus the diagonal of Lambda Phi Lambda’), which accounts for the factor correlations.
• The subscale omega footnotes and the compute_indices() help describe the other factor’s variance as an additional source of error rather than as partialled out (Morin et al., 2020).
• print() of the reliability indices follows the console width (80 to 100 columns) instead of a fixed 100, and alignment_check() wraps its recommendation line.

Measurement invariance

• The “Fitting …” line of esem_invariance() is printed in bold blue where the console supports ANSI colour (RStudio, or a terminal whose TERM is not “dumb”); options(bifactory.ansi_colour = FALSE) turns it off, TRUE forces it. Same detection as parameters().
• esem_invariance() catches lavaan’s estimation warnings per level, on the master and on the worker processes, and reports them reworded in inv$notes and under “Estimation notes” after the table. Admissibility is read from the reported solution, so a note names the group and the parameter, e.g. “a negative variance estimate (Heywood case): 2 (G latent variance -0.120)”. Only the reported fit’s notes are kept; package warnings are unaffected.
• A closing block ends every run and print(): levels fitted and considered, that the table can be interpreted, the most constrained admissible level supported by dCFI >= -0.010 among all fitted levels, any note at that level, a tip toward through = "varcov" / "means" or partial_invariance() when strict is supported but inadmissible, and “Remember: print(inv)”. factor_scores(level = "auto") uses the same rule, so it never selects an inadmissible level and can select varcov or means when they were fitted.
• esem_invariance() gains through = c("strict", "varcov", "means"): the latent variance/covariance and latent mean invariance levels of Morin’s sequence, for ESEM and B-ESEM under MLR and WLSMV. The default sequence is unchanged; run_mplus_besem_invariance() mirrors the fitted levels.
• partial_invariance() follows the partial-invariance rules for ESEM and B-ESEM. Only level = "strong" (intercepts or thresholds) and level = "strict" (residual variances) are accepted; level = "weak" is refused with an explanation, because the rotated loadings are constrained as a block. Constraints are released one at a time by score test; an item is released only if every factor it belongs to keeps at least two items with invariant intercepts/thresholds (Byrne, Shavelson & Muthén, 1989; van de Schoot, Lugtig & Hox, 2012); releasing more than 20% of the constraints added at a level warns (Dimitrov, 2010); every released parameter is listed. On ordinal items at least one threshold per item stays invariant (Millsap & Yun-Tein, 2004); an item’s last threshold can be released by hand through esem_invariance(..., group.partial = "item|t1"). Released thresholds are honoured on the ordinal path, the continuous refit is retried from simple starting values, and B-ESEM is supported. A recovery test plants intercept shifts on two items in one of two simulated groups and checks that exactly those items are released, as intercepts on the continuous path and as thresholds on the ordinal path.
• The ordinal multi-group configural model is fitted from the per-group optima: each group is fitted alone from two starts and the joint fit starts from those values, passed as a parameter table. Every other level is fitted from lavaan’s default and its start = "simple" starting values; the alternative is kept when its fit function is lower by more than 0.1%. The new cores argument (default 2) runs the two starts on two worker processes at the same time with identical results, so a level takes as long as its slower start; cores = 1 fits sequentially.
• align_loadings() compares against another fit, or against a supplied solution (lambda, psi, theta per group), by orientation transfer: the unstandardized loadings are rotated to the reference and the factor covariances are transformed with the same rotation before standardizing. This is exact in every group, including groups with free factor covariances, where Procrustes alignment of standardized loadings is not. An esem_invariance target is read at the requested level.
• run_mplus_besem_invariance() writes CONVERGENCE = 0.000001 for its first Mplus attempt; if Mplus does not converge there, the retries start at Mplus’s default and then loosen (1e-4 to 5e-2). When a level’s Mplus run prints no fit (singular information matrix, no DIFFTEST derivatives file), DIFFTEST is omitted from the next level’s input. extract_mplus_loadings() returns numeric matrices for such outputs.

bifactory 0.5.2

This release contains defensive fixes; estimation results are unchanged.

• parameters() on a Heywood-corrected ESEM fit now reports NA for standard errors, z-values, and p-values when the rotation changed after those quantities were computed, while retaining the corrected standardized loadings.
• Reliability calculations floor residual variances at 1e-6, preventing a Heywood case from producing a negative residual variance and corrupting the H index.
• factor_scores() now raises an informative error when the polychoric correlation or score-information matrix is singular, instead of exposing a bare solve() failure.
• Heywood retries now recognize the NA/0 target convention, so primary cells in targets built that way are freed correctly.
• B-ESEM sign correction now follows the target column order before orienting loadings, rather than assuming that the general factor is the first column.
• factor_scores() now warns when one pooled polychoric matrix is applied across multiple groups.
• esem_ordered() and besem_ordered() now stop with a clear message when supplied item names collide case-insensitively, instead of silently mismatching them.
• The ECV index now returns NA rather than NaN for a degenerate all-zero loading matrix.
• The RMSEA confidence-interval upper bound retries with a wider bracket only when the original search fails, leaving previously published values unchanged when the original search succeeds.

bifactory 0.5.1

Changes in response to CRAN review (no changes to estimation results):

• DESCRIPTION: all acronyms are now spelled out on first use (WLSMV, MLR, DWLS, ICM-CFA); removed quotes around efa().
• Console output outside print()/summary() methods now uses message() (or warning() where appropriate) instead of cat()/print(), so it can be suppressed with suppressMessages(). Progress output keeps its verbose gating.
• parameters() now returns a classed data frame (bifactory_parameters) that prints the same formatted table via its own print() method. Assigning the result no longer prints as a side effect.
• Random-number state is no longer saved to and restored from .GlobalEnv; internal fixed-seed sections use withr::with_seed() (new Import: withr). Draws are unchanged, so results are identical to 0.5.0.
• Examples rewritten to be self-contained and executable (lavaan::HolzingerSwineford1939); \dontrun{} is retained only for examples that require a licensed Mplus installation or open an interactive editor. Longer-running examples use \donttest{}. No runnable example uses a package from Suggests.

bifactory 0.5.0

• Initial CRAN submission.

Features

• Bifactor ESEM (B-ESEM), standard ESEM, and CFA for continuous and ordered-categorical data.
• Continuous models via ‘lavaan’ native efa() blocks (MLR).
• Ordered-categorical ESEM via ‘lavaan’ WLSMV; ordered B-ESEM via a custom diagonally weighted least squares (DWLS) path with polychoric correlations from ‘psych’, rotation-delta standard errors via ‘numDeriv’, and mean-and-variance-adjusted chi-square.
• Target, geomin, and oblimin rotations via ‘GPArotation’; the bifactor ESEM approach follows Morin, Arens and Marsh (2016).
• Multi-group measurement invariance (configural through strict, with partial invariance), ESEM-within-CFA conversion, McDonald’s omega reliability suite, and the Mehrvarz and Rouder (2026) alignment-ratio check for ICM-CFA misspecification.
• Optional side-by-side comparison with Mplus output via ‘MplusAutomation’.