Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 361

The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.

Subgrouping Poor Readers on the Basis of Individual Differences in Reading-Related Abilities

Open access
Catts, Hugh W., Hogan, Tiffany P., Fey, Marc E.·2003·Journal of Learning Disabilities

Abstract

The present study investigated the use of the Reading Component Model to subgroup poor readers. A large sample of poor readers was identified in second grade and subgrouped on the basis of relative strengths and weaknesses in word recognition and listening comprehension. Although homogeneous subgroups were not identified, poor readers could be classified into four subgroups that differed significantly in reading-related abilities. Further analyses showed that poor readers' strengths and weaknesses in listening comprehension, and to a lesser extent in word recognition, were foreshadowed by their abilities on related kindergarten measures. Follow-up testing in the fourth grade indicated that poor readers' individual differences in word recognition and listening comprehension were consistent and that subgroups were moderately stable. The implications of these results for the assessment and remediation of reading disabilities are discussed.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1177/002221940303600208

Cites

67 of 67 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 67 references

Cited by

See all 361

Metadata

Authors
Catts, H. W., Hogan, T. P., & Fey, M. E.
Venue
Journal of Learning Disabilities
Published
2003-03
Volume
36
Issue
2
Pages
151-164
ISSN
  • 0022-2194 (ISSN-L)
  • 1538-4780
OpenAlex
W2153079195
Cited by
361
References
67
FWCI
10.92
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Subgrouping Poor Readers on the Basis of Individual Differences in Reading-Related Abilities. https://app.cochat.ai/papers/10.1177/002221940303600208
The paper
Catts, H. W., Hogan, T. P., & Fey, M. E. (2003). Subgrouping Poor Readers on the Basis of Individual Differences in Reading-Related Abilities. Journal of Learning Disabilities. https://doi.org/10.1177/002221940303600208

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.