A correlated-strengths extension of the dual-memory model with correlation parameter ρ = .334 fits the high-relatedness mean and distribution data¶

Claim · All claims
Evidence · 1 study · causal r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Simulation incorporating a free parameter ρ for the correlation between study and test memory strengths yielded a best fit at ρ = .334, which fit the mean data and the bulk of the distribution for high relatedness items. → Gupta 2026

Evidence¶

Gupta 2026¶

Gupta, M.W., Pan, S.C., & Rickard, T.C. (2026). Semantic relatedness and the efficacy of retrieval practice. npj Science of Learning. https://doi.org/10.1038/s41539-026-00416-8

q2 · i? · causal · r2

Simulation extension of the dual-memory model adding one free parameter ρ representing study–test memory strength correlation. The article reports "The best fit to the mean data was obtained for ρ = .334" with a good distribution fit shown in Figure 5b; no effect size is printed.

"The best fit to the mean data was obtained for ρ = .334, for other ρ fits, see Supplementary Figure 2. And as shown in Figure 5b, that value of ρ yielded a good fit across the bulk of the distribution for high relatedness items."

Discussion¶

Related Claims¶

• Model-based analysis shows the relative efficacy of testing is reduced for highly related word pairs, with the dual-memory model overpredicting test performance only in the high-relatedness group — related
• Cumulative distribution analysis shows the dual-memory model systematically overpredicts test performance at all restudy levels for high-relatedness pairs, ruling out a participant-level ceiling effect — related