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Identifiability, State Separation, and Label Uncertainty

State labels are anchored through ordered RT deviations only as an identification convention. This ordering does not order psychological meaning.

sim <- simulate_multimodal_m4(n_person = 30, n_item = 8, scenario = "weak", seed = 20260820)
audit_multimodal_m4_identifiability(sim, include_posterior = FALSE)
#> <eye_multimodal_m4_identifiability>
#>   overall: REVIEW
#>            domain                        criterion status severity value
#>          sequence                   sequence_count   PASS     none    30
#>          sequence          minimum_sequence_length   PASS     none     8
#>          sequence                 transition_count   PASS     none   210
#>              data                response_observed   PASS     none   240
#>              data                      rt_observed   PASS     none   240
#>              data                    gaze_observed   PASS     none   240
#>              data                   pupil_observed   PASS     none   240
#>              data maximum_process_missing_fraction   PASS     none     0
#>  model_complexity         trait_conditioned_markov REVIEW moderate     2
#>                                     threshold
#>                                 >=2 preferred
#>                                           >=2
#>                                          >=20
#>                                            >0
#>                                            >0
#>                                            >0
#>                                            >0
#>                              <=0.50 preferred
#>  0 transition traits for unconditional Markov
#>                                                                                                                                               message
#>                                                                                                              Number of independent ordered sequences.
#>                                                                                           Shortest sequence relative to declared fitting requirement.
#>                                                                                                                Available within-sequence transitions.
#>                                                                                                                       Observed response measurements.
#>                                                                                                                             Observed rt measurements.
#>                                                                                                                           Observed gaze measurements.
#>                                                                                                                          Observed pupil measurements.
#>                                                                                                             Largest process-channel missing fraction.
#>  Trait-conditioned Markov dynamics add person-level process slopes whose posterior identification cannot be established from structural counts alone.
#>                                                                                                                                                           recommendation
#>                                                                                                     Use multiple persons/sequences for population-level state inference.
#>                                                                                            Do not silently discard short sequences; revise design or explicit threshold.
#>                                                                                          Transition parameters may be prior-dominated when few transitions are observed.
#>                                                                                            M4 cannot identify the requested response contribution without observed data.
#>                                                                                                  M4 cannot identify the requested rt contribution without observed data.
#>                                                                                                M4 cannot identify the requested gaze contribution without observed data.
#>                                                                                               M4 cannot identify the requested pupil contribution without observed data.
#>                                                                                       Study missingness sensitivity; M4 reference fitting assumes ignorable missingness.
#>  Treat this specification as gated: require satisfactory posterior R-hat/ESS, stable state occupancy across chains, and separated state emissions before interpretation.
states <- multimodal_m4_state_diagnostics(sim)
states
#> <eye_multimodal_m4_states>
#>   source: synthetic_truth
#>   states: 2
#>   mean entropy: 8.003e-15
#>   mean MAP run length: 3.478
#>   boundary: MAP labels are secondary summaries; posterior probabilities carry uncertainty

Posterior entropy, occupancy, transition structure, emission separation, and contextual associations should be inspected together before any substantive interpretation.

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.