Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 16

The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.

The substantiveness of socioeconomic school compositional effects in Australia: measurement error and the relationship with academic composition

Sciffer, Michael G., Perry, Laura B., McConney, Andrew·2022·Large-scale Assessments in Education

Published version of a preprint

Abstract

This study examines the effect of school socioeconomic composition on student achievement growth in Australian schooling, and its relationship with academic composition utilising the National Assessment Program—Literacy and Numeracy (NAPLAN) dataset. Previous research has found that school composition predicts a range of schooling outcomes. A critique of school compositional research has been that measurement error may have biased findings of compositional effects. Prior studies have found that socioeconomic compositional effect sizes are small when models include academic composition. The relationship between socioeconomic and academic compositions has yet to be fully determined. Multi-level regressions and structural equation models were compared to estimate the degree of bias in socioeconomic compositional effects due to measurement error. Multi-level path models were used to test if academic composition mediated the relationship between socioeconomic composition and achievement growth. The results showed that measurement error did not bias compositional effects in the dataset, and academic composition mediates the relationship between socioeconomic composition and achievement growth. We argue that school value-add research should include academic composition to account for contextual effects. The socioeconomic compositional effect is of practical significance to policy makers and educational researchers due to its relative size compared to average student achievement growth. Potential reforms include ensuring public subsidies to private schools in Australia do not increase school segregation and the amelioration of the effects of residential segregation through school funding reforms.

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 · 10.1186/s40536-022-00142-8

Cites

73 of 73 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 73 references

Research works printed but not linked: 3

  1. Greenwell, T., & Bonnor, C. (2022). Waiting for Gonski: How Australia failed its schools. University of New South Wales Press.
  2. Muthén, L. K., & Muthén, B. O. (2017). Mplus user’s guide (8th ed.). Muthén & Muthén.
  3. Organisation for Economic Co-operation and Development. (2017). PISA 2015 technical report. OECD.

Cited by

See all 16

Metadata

Authors
Sciffer, M. G., Perry, L. B., & McConney, A.
Venue
Large-scale Assessments in Education
Published
2022-11-23
Volume
10
Issue
1
ISSN
2196-0739
Cited by
16
References
73
Language
en
Licence
Funders
Australian Government Research Training Program

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: The substantiveness of socioeconomic school compositional effects in Australia: measurement error and the relationship with academic composition. https://app.cochat.ai/papers/10.1186/s40536-022-00142-8
The paper
Sciffer, M. G., Perry, L. B., & McConney, A. (2022). The substantiveness of socioeconomic school compositional effects in Australia: measurement error and the relationship with academic composition. Large-scale Assessments in Education. https://doi.org/10.1186/s40536-022-00142-8

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.