feat(psychometric): recover Driver p.16 asymTIPREDEFFECTstd after positive variances

[seonghobae]

Stacked on #190 (adb0bc6) / #189 (0836c35) / #188 (444304d) / #187 (6afd048) / #185 (69ffec6) / #184 (6b93147) / #183 (c10097be) / #182 (2d4d6bf) / #181 (542806b) / #49 (6f95142). ADR 0005 executable slice stays inside psychometric_core. This is not a second invariance crate and does not recreate #78 or #80.

psychometric_core recovers the Driver, Oud, and Voelkle (2017, p. 16 asymTIPREDEFFECTstd; §7.2, pp. 20–21; Eq. 3, p. 5; Table 2, p. 12; footnote 4; JSS PDF re-opened 2026-08-23T14:25Z from https://www.jstatsoft.org/index.php/jss/article/download/v077i05/1104) scalar standardised asymptotic time-independent predictor effect. Page 16 prints continuous-time parameters and, when appropriate, standardised matrices with the suffix std. Section 7.2 names asymTIPREDEFFECT the expected total change in process means given a unit increase on a time-independent predictor. The scalar map is -B / a for stable a < 0. Footnote 4: standardisations use only the relevant variance, not the total. The affecting variance is predictor variance TIPREDVAR v. The affected variance is within-subject asymDIFFUSION -q / (2 a), because the process dynamics are individual, or average individual, temporal dynamics.

Form strictly positive asymDIFFUSION first, then strictly positive v, then the unit asymptotic effect, then (-B / a) · √v / √(-q / (2 a)).

• Unstandardised -B / a is defined for a zero coefficient and for zero predictor variance; standardised asymTIPREDEFFECT is not.
• Zero asymDIFFUSION has no positive process SD and fails closed (StandardisedAsymptoticTimeIndependentEffectRequiresPositiveWithinSubjectVariance).
• Zero TIPREDVAR has no positive predictor SD and fails closed (StandardisedAsymptoticTimeIndependentEffectRequiresPositivePredictorVariance).
• a ≥ 0 cannot form finite asymDIFFUSION and fails closed (StationaryVarianceRequiresStableDrift).
• The finite-interval standardisation A^{-1}[e^{A Δt} − I] B · √v / √p depends on the event interval and is not asymTIPREDEFFECTstd.
• Section 7.1 warns that omitting trait variance confounds between- and within-person information. (-B / a) · √v / √(trait + p + added) uses the total, not asymDIFFUSION, and is not asymTIPREDEFFECTstd when TRAITVAR is nonzero.
• TRAITVAR is not the footnote 4 standardisation variance.

Still not a Kalman filter, not a matrix expm, not ESEM estimation, not DSEM, and not ctsem estimation. Meredith (1993) remains unread (Unpaywall 2026-08-23T13:19Z: is_oa: false; title Measurement Invariance, Factor Analysis and Factorial Invariance). Mislevy (1991, Psychometrika, 56, 177–196) remains unread (Unpaywall 2026-08-23T13:19Z: is_oa: false; title Randomization-Based Inference about Latent Variables from Complex Samples).

Do not merge, self-approve, or request Copilot.

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