NEWS
slca 1.4.1
- Fixed saturated-frequency handling for partially missing data when missing patterns map to candidate observed cells of equal length.
- Updated internal response encoding to use
-1 for missing values and zero-based category indices for C++ calculations.
- Kept simulated manifest responses as plain factor data frames without internal encoding attributes.
- Fixed
predict.slcafit() when newdata is omitted.
- Added validation for
predict() inputs, simulation levels, and initial parameter lengths.
- Added validation for model formulas, regression latent outcomes, bootstrap counts, and simulation counts.
- Fixed simulated factor responses when some generated categories are absent in a sample.
- Fixed Hessian-based covariance extraction and regression confidence interval returns.
- Fixed regression standard errors and Wald p-values in
summary.reg.slca().
- Hardened
gof() list calls and bias-adjusted regression internals.
- Recorded bootstrap replicate failures in model-fit diagnostics instead of returning error objects.
- Clarified the documented structure of
convergence, predict(), and simulated responses.