Evidence map›Paper›PMID 31950361›Full record

ArticleBehavior research methods2020

Using information-theoretic measures to characterize the structure of the writing system: the case of orthographic-phonological regularities in English.

Noam Siegelman, Devin M Kearns, Jay G Rueckl

Abstract read
In one paragraph

Article in Behavior research methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. How we should measure orthographic depth: Or should we?Psychonomic bulletin & review · 2026
    Review
  2. Article
  3. Statistical learning in spelling and reading.Trends in cognitive sciences · 2025
    Review
  4. Article
  5. Article
  6. HeLP: The Hebrew Lexicon project.Behavior research methods · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Predicting Later Spelling from Kindergarten Spelling in U.S., Australian, and Swedish Children.Scientific studies of reading : the official journal of the Society for the Scientific Study of Reading · 2023
    Article
  14. Article
  15. Article
  16. Article
  17. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Noam SiegelmanHaskins Laboratories, New Haven, CT, 06511, USA. noam.siegelman@yale.edu.
Devin M KearnsHaskins Laboratories, New Haven, CT, 06511, USA.
Jay G RuecklHaskins Laboratories, New Haven, CT, 06511, USA.

Funding

Visual word identification: phonology &morphologyP01HD001994 · NICHD · HASKINS LABORATORIES, INC. · PI MENCL, EINAR · 1985 to 2016
$23.5M
Tracking neurocognitive changes during evidence-based reading instruction in typically and atypically developing childrenR37HD090153 · NICHD · UNIVERSITY OF CONNECTICUT STORRS · PI Kenneth R. Pugh · 2017 to 2026
$6.0M
Predictors of Non- Response in Young Dyslexic Children with Co-Morbid ADHDP01HD070837 · NICHD · GEORGIA STATE UNIVERSITY · PI ZEVIN, JASON D · 2013 to 2018
$4.6M
Experiential and child factors that determine acquisition of orthographic-phonological regularities in a quasi-regular writing system: An integrated behavioral/computational/neurobiological approachP20HD091013 · NICHD · FLORIDA STATE UNIVERSITY · PI COMPTON, DONALD L · 2017 to 2025
$4.2M
NICHD NIH HHS P01 HD001994NICHD NIH HHS P01 HD070837NICHD NIH HHS P20 HD091013NICHD NIH HHS R37 HD090153
6 · The paper itself

Abstract

It is generally well accepted that proficient reading requires the assimilation of myriad statistical regularities present in the writing system, including in particular the correspondences between words' orthographic and phonological forms. There is considerably less agreement, however, as to how to quantify these regularities. Here we present a comprehensive approach for this quantification using tools from Information Theory. We start by providing a glossary of the relevant information-theoretic metrics, with simplified examples showing their potential in assessing orthographic-phonological regularities. We specifically highlight the flexibility of our approach in quantifying information under different contexts (i.e., context-independent and dependent readings) and in different types of mappings (e.g., orthography-to-phonology and phonology-to-orthography). Then, we use these information-theoretic measures to assess real-world orthographic-phonological regularities of 10,093 mono-syllabic English words and examine whether these measures predict inter-item variability in accuracy and response times using available large-scale datasets of naming and lexical decision tasks. Together, the analyses demonstrate how information-theoretical measures can be used to quantify orthographical-phonological correspondences, and show that they capture variance in reading performance that is not accounted for by existing measures. We discuss the similarities and differences between the current framework and previous approaches as well as future directions towards understanding how the statistical regularities embedded in a writing system impact reading and reading acquisition.

Indexed as

PhoneticsWritingData CollectionReaction Timeinformation theoryorthography-to-phonology transparencyprint-speech correspondencesreadingword recognition

Identifiers

PMID31950361
PMCPMC7286800

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.