Results provide no support for the IQ-achievement discrepancy model of dyslexia; non-verbal IQ correlated with all Year-1 language measures¶
Claim · All claims
Evidence · 1 study · associationalr2·q2
Currency · newest study 2017 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? Deficit groups did not show average IQ with low language skills; instead non-verbal IQ was significantly positively correlated with all Year 1 measures (e.g., PA r = .344). → Ozernov-Palchik 2017
Evidence¶
Ozernov-Palchik 2017¶
Ozernov-Palchik, O., Norton, E. S., Sideridis, G., Beach, S. D., Wolf, M., Gabrieli, J. D. E., & Gaab, N. (2017). Longitudinal stability of pre-reading skill profiles of kindergarten children: Implications for early screening and theories of reading. Developmental Science. https://doi.org/10.1111/desc.12471
q2 · i? · associational · r2
Pearson correlations between the KBIT-2 Matrices measure and Year 1 measures in the full sample; the article prints "Pearson r estimates with PA = .344, p<.001, with LSK = .140, p<.001, with RAN = .226, p<.001, and with NWR = .276".
"In fact, the non-verbal IQ scores were significantly correlated with all Year-1 language measures, indicating a strong coupling between general cognitive abilities and reading."
Discussion¶
Learner Variables¶
- General Cognitive Ability — predictor: learners who differ on it differ in outcomes
- Learning Disabilities and Developmental Differences — predictor: learners who differ on it differ in outcomes
Related Claims¶
- Kindergarten profile membership predicts differentiated 1st-grade reading patterns: the double-deficit group performed worse than all other profiles on nearly all measures — related
- Non-verbal intelligence measures (Raven, WISC Block Design) are non-significant math predictors when well-specified spatial and memory measures are in the model — related
- Age predicts decoding efficiency in children with dyslexia while working memory and perceptual organization covariate effects are non-significant — related
- Cascade models in which IQ mediates the WM-to-achievement path fit comparably to, but not significantly better than, the original correlated models — related
- PA and RAN deficit profiles are over-represented in low-SES schools, while the double-deficit profile distribution is proportional to school SES group size — related
- Latent profile analysis of kindergarten pre-reading measures yields six distinct performance profiles, including PA risk, RAN risk, and double-deficit risk groups — related
- IQ and working memory are reliable predictors of academic achievement at the beginning of school when domain knowledge is not controlled — related
- Crowding effects, pre-cue dependence and set size effects each correlate significantly with reading and spelling measures — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
no-support-iq-discrepancy-model |
title |
Results provide no support for the IQ-achievement discrepancy model of dyslexia; non-verbal IQ correlated with all Year-1 language measures |
description |
Results provide no support for the IQ-achievement discrepancy model of dyslexia; non-verbal IQ correlated with all Year-1 language measures |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2017 |
source_checked |
2026-10-20 |
generated |
by process:wiki-ingest on 2026-10-17 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — ozernov-palchik-2017 |
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