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compute_assurance() function for unconditional
Bayesian assurance (O’Hagan & Stevens, 2001) computed as a weighted
average of conditional power over a design prior on the effect
size.assurance_prior_weights() convenience wrapper for
constructing normalised design-prior weights (normal, uniform, beta)
over an effect grid.decide_sample_size() function with both assurance
mode (design prior) and conditional mode for recommending sample sizes
from simulation output.validate_inla_vs_brms() function for spot-checking
INLA posterior estimates against brms/Stan.brms_inla_power,
powerbrmsINLA_assurance, and
powerbrmsINLA_sample_size objects.plot_assurance_curve() and
plot_assurance_with_robustness() for unconditional
assurance visualisation.plot_bf_assurance_curve_smooth(),
plot_bf_assurance_curve(),
plot_bf_expected_evidence(), and
plot_bf_heatmap() for Bayes factor visualisation.plot_decision_assurance_curve(),
plot_decision_threshold_contour(), and
add_decision_overlay() for decision-rule
visualisation.plot_design_prior() for visualising design
priors.plot_interaction_surface() for multi-effect grid
visualisation.plot_power_contour(),
plot_power_heatmap(), and
plot_power_assurance_overlay() for conditional power
visualisation.plot_precision_assurance_curve() and
plot_precision_fan_chart().brms_inla_power() now supports multi-effect grids
(data.frame effect_grid), brms-to-INLA prior translation
with full audit trail, marginal-likelihood Bayes factors
(bf_method = "marglik"), and automatic INLA thread
detection.brms_inla_power_sequential() rewritten with
multi-effect support and prior translation.brms_inla_power_two_stage() now uses the modernised
engine internally..to_inla_family(),
.scale_fill_viridis_discrete()).requireNamespace("MASS") guard for negative
binomial data generation..Rbuildignore to exclude
.claude/, .DS_Store, .Rcheck/,
and .tar.gz artefacts.brms_inla_power_parallel() for parallel
simulations.decide_sample_size() and
add_decision_overlay() helpers.error_sd and group_sd now accept
distributional specifications (halfnormal,
lognormal, uniform) for variance-uncertainty
integration; new validate_sd_spec() helper exported.test-validation-classical.R,
test-validation-bayesassurance.R) and accompanying vignette
benchmarking against power.t.test() and
bayesassurance::assurance_nd_na()..github,
LICENSE.md, and cran-comments.md from the
source tarball via .Rbuildignore.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.
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