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M4 is evaluated incrementally against M3 rather than assumed to be useful. The core comparison is M3 versus M4, with K=1 and no-trait-conditioning models used as focused diagnostic references.
sim <- simulate_multimodal_m4(n_person = 30, n_item = 8, seed = 20260820)
multimodal_m4_ablation(sim)
#> <eye_multimodal_m4_ablation>
#> executed: FALSE
#> target: response-target predictive evidence
#>
#> model K transition traits state_channels
#> M3 NA <NA> <NA> <NA>
#> M4_K1 1 markov none rt+gaze+pupil
#> M4_K2 2 markov theta+tau rt+gaze+pupil
#> M4_K2_NO_TRAIT 2 markov none rt+gaze+pupil
#> M4_K2_IID 2 iid theta+tau rt+gaze+pupil
#> question
#> validated M3 baseline
#> formal K=1 null
#> reference M4 increment
#> does trait conditioning matter?
#> does sequential dependence matter?Response-target ELPD and uncertainty changes are interpreted as predictive/inferential evidence, not causal effects.
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.