Academic Journal
Q1British Journal of Mathematical and Statistical Psychology
About British Journal of Mathematical and Statistical Psychology
About British Journal of Mathematical and Statistical Psychology
British Journal of Mathematical and Statistical Psychology is a peer-reviewed scholarly journal published by Wiley-Blackwell (United States). It focuses on Q1. Publication coverage spans 1965-2026.
Key indicators: ISSN 0007-1102, 2044-8317; H-index 69.
Understanding This Journal's Metrics
Journal metrics help researchers assess fit, but they must be interpreted in context:
- H-index (69): Strong citation impact — 69 articles cited at least 69 times each, reflecting solid influence.
Publishing in British Journal of Mathematical and Statistical Psychology
An established venue in its field. The journal welcomes solid, well-executed research. Ensure your manuscript fits the stated scope and follows author guidelines carefully.
- Scope fit: Confirm your research aligns with Q1. Off-scope manuscripts are typically desk-rejected quickly.
- Author guidelines: Follow formatting, reference style, and article-type requirements exactly — non-compliant manuscripts may be returned without review.
- Submission: Submit via the official journal website.
Is This Journal Right for Your Paper?
- Audience match: Will the journal's readers cite and build on your findings?
- Timeline: Higher-tier journals mean longer review and higher rejection risk. Balance prestige against your schedule.
- Indexing: Confirm indexing in Web of Science, Scopus, and PubMed (if biomedical) meets your institutional requirements.
- Open access needs: Check funder mandates and whether the journal offers compliant OA options.
Frequently Asked Questions
What is the ISSN of British Journal of Mathematical and Statistical Psychology?
0007-1102, 2044-8317.
Who publishes British Journal of Mathematical and Statistical Psychology?
Wiley-Blackwell.
What are British Journal of Mathematical and Statistical Psychology's metrics?
H-index 69.
Where do I submit to British Journal of Mathematical and Statistical Psychology?
Via the official website.
Is British Journal of Mathematical and Statistical Psychology peer-reviewed?
Yes — it is a peer-reviewed scholarly journal indexed in major academic databases.
Source-backed journal facts
Topics in published research
Advanced Statistical Methods and Models; Statistical Methods and Bayesian Inference; Psychometric Methodologies and Testing; Advanced Statistical Modeling Techniques; Sensory Analysis and Statistical Methods; Multi-Criteria Decision Making.
OpenAlex classifies topics from published works. These topics are not the publisher’s official aims and scope.
Reported open-access list prices
3,400.00 USD; 2,850.00 EUR; 2,270.00 GBP
APC list prices reported by OpenAlex, which obtains this information from DOAJ. Confirm current charges, taxes, waivers and eligibility with the publisher; this is not a fee quotation.
Source: OpenAlex source record. Retrieved 2026-10-03. Source record updated 2026-10-02. OpenAlex metrics are different from SCImago metrics and the Clarivate Journal Impact Factor.
Journal Metrics
Quartile, SJR and the listed SCImago H-index use the 2025 imported SCImago dataset. A quartile may vary by subject category. Values without a source or reporting year are unverified historical entries. Verify the current Journal Impact Factor with Clarivate or the publisher before using it.
Aims & Scope
The publisher’s official aims and scope have not yet been verified for this profile. Use the journal website to check subject fit and accepted article types before submitting.
Recent Research Articles
Latest publications matched automatically by ISSN.
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2026-10-16 · DOI: 10.1111/bmsp.70080A taxonomy of reliability indices for cluster‐level constructs measured by multiple individual‐level indicators
Terrence D. Jorgensen, Suzanne Jak
2026-10-14 · DOI: 10.1111/bmsp.70074Model fit and parameter uncertainty in amortized variational inference based item response theory
K. Veldkamp, R. P. P. P. Grasman, R. Debelak, D. Molenaar et al.
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L. Andries van der Ark, Terrence D. Jorgensen
2026-10-01 · DOI: 10.1111/bmsp.70077Kurtosis‐robust estimation of the fixed effects eta‐squared: An impossibility theorem for F ‐based estimators and a practical correction
Daiki Nakamura
2026-09-30 · DOI: 10.1111/bmsp.70075A regularised latent‐class item response model for detecting measurement non‐invariance in ordinal response scales
Gabriel Wallin, Qi Huang
2026-09-30 · DOI: 10.1111/bmsp.70076Detecting differential item functioning with unknown subgroups and anchor items in cognitive diagnostic assessment
Zhilin Song, Qing Zeng, Ping Chen
2026-08-30 · DOI: 10.1111/bmsp.70073Sensitivity analysis for unmeasured pretreatment confounders in causal mediation analysis with debiased machine learning
Xiao Liu, Cameron McCann
2026-08-28 · DOI: 10.1111/bmsp.70072Geometric standardized mean difference and its application to meta‐analysis
Jiandong Shi, Xiaochen Zhang, Lu Lin, Hiu Yee Kwan et al.
2026-08-17 · DOI: 10.1111/bmsp.70071A Bayesian framework for the logistic positive exponent and its reflection IRT models
Jorge González, Jorge Bazán, Isidora Colil‐Celis
2026-08-06 · DOI: 10.1111/bmsp.70070Calibrating Bayesian inference
Yang Liu, Jonathan P. Williams, Jan Hannig
2026-07-30 · DOI: 10.1111/bmsp.70065Multidimensional unipolar IRT and applications to the measurement of print exposure
Qi (Helen) Huang, Daniel M. Bolt
2026-07-22 · DOI: 10.1111/bmsp.70067On the asymmetry, complexity and predicted data patterns of nontraditional item response theory models
Hyejin Shim, Wes Bonifay
2026-07-16 · DOI: 10.1111/bmsp.70069Estimation of comparable standardized mean differences in cluster randomized trials with covariate adjustment
Juyoung Jung, Zhijiang Liu, Ariel M. Aloe
2026-07-15 · DOI: 10.1111/bmsp.70062Revisiting reliability and measurement precision: Towards a unified perspective
Jimmy de la Torre, Klaas Sijtsma, Rodrigo Schames Kreitchmann
2026-07-15 · DOI: 10.1111/bmsp.70068New estimation methods for diagnostic classification models
Elena Castilla
2026-07-13 · DOI: 10.1111/bmsp.70064Mixture multigroup structural equation modelling for ordinal data
Andres F. Perez Alonso, Jeroen K. Vermunt, Yves Rosseel, Kim De Roover et al.
2026-07-12 · DOI: 10.1111/bmsp.70061Review of cognitive diagnostic models ( CDMs ): Recent methodological advancements for addressing practical challenges
Chun Wang, Yale Quan, David Arthur
2026-07-11 · DOI: 10.1111/bmsp.70066Refining effect size measures and classification for differential item functioning: Toward unified guidelines across methods
Michaela Cichrová, Adéla Hladká, Patrícia Martinková
2026-07-10 · DOI: 10.1111/bmsp.70060Connections between the basic local independence model and true and error models in the study of preference
Luca Stefanutti, Andrea Brancaccio, Debora de Chiusole
2026-07-08 · DOI: 10.1111/bmsp.70063Reviews
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Version History
October 9, 2026 at 8:03 pm
September 25, 2026