The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
congruence_test() now attaches each congruence
coefficient — and its bootstrap SD, t-statistic, and confidence interval
— to the correct construct pair. Coefficients were generated in
combn() (row-major) order but written into the results
matrix via upper.tri() (column-major) order; the two
orderings diverge for models with four or more constructs, which
mislabelled non-adjacent pairs (e.g. COMP <> CUSL and
LIKE <> CUSA were swapped in the simple
corporate-reputation model, and 10 of 15 pairs were mislabelled in the
six-construct example). The coefficient values themselves were correct;
only their pair labels were wrong. Added a regression test asserting
pair-label correctness against an independent name-indexed
reference.test-cipma-comprehensive.R and
test-fimix.R no longer reach into seminr’s non-exported
internals via seminr:::items_of_construct() and
seminr:::all_endogenous(). They now use seminrExtras’s own
local helpers of the same name. This avoids breakage against forthcoming
seminr 2.5.0, which refactors (and renames) those internal helpers.Composite Overfit Analysis (COA):
assess_coa(), predictive_deviance(),
deviance_tree(), unstable_params(),
group_rules(), competes() for diagnosing
why and for whom PLS models fail to generalise
out-of-sample.
Necessary Condition Analysis (NCA):
assess_nca() with fully internal CE-FDH and CR-FDH
algorithms (no external NCA package dependency).
NCA-ESSE: assess_nca_esse()
implements the effect size sensitivity extension (Becker et al.,
2026).
Combined Importance-Performance Map Analysis
(cIPMA): assess_cipma() integrates IPMA with NCA
to classify constructs into actionable priority quadrants.
assess_ipma() provides an IPMA-only convenience wrapper.
Supports HOC, mediation, and moderation models.
FIMIX-PLS: assess_fimix() and
assess_fimix_compare() for EM-based latent class
segmentation with multi-start initialisation and information criteria
comparison.
PLS-POS: assess_pos(),
assess_pos_compare(), and pos_segments() for
prediction-oriented segmentation that maximises the sum of R-squared
across segments (Becker et al., 2013).
CTA-PLS: assess_cta() for
confirmatory tetrad analysis with automatic indicator borrowing for
constructs with fewer than 4 indicators (Gudergan et al.,
2008).
Predictive Contribution of the Mediator (PCM):
assess_pcm() evaluates whether a mediating construct
improves out-of-sample prediction by comparing DA and EA approaches on
isolated sub-models (Danks, 2021).
assess_cvpat() and
assess_cvpat_compare(): fixed bootstrap test branches, loss
function return types, and reference metadata.
congruence_test(): fixed division guard,
upper-triangular masking, and bootstrap robustness for
nboot = 0.
All features include print(),
summary(), and plot() S3 methods.
Comprehensive test suite (740+ tests).
Demo files for all features:
demo("seminr-pls-<feature>").
Updated vignette with examples for all features.
seminr >= 2.4.0.rpart added to Imports (for COA deviance trees).MASS, paran, psych,
learnr added to Suggests.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.