Journal of Applied Statistics Citation Rate 2026
0266-4763
eISSN 1360-0532
Taylor & Francis
GB
Q3 Quartile
About Journal of Applied Statistics
Journal of Applied Statistics (JAS) is a peer-reviewed academic journal covering Advanced Statistical Methods and Models and Advanced Statistical Process Monitoring, published by Taylor & Francis in GB, catalogued under ISSN 0266-4763 (e-ISSN 1360-0532). As of 2026, it has a 2025 2-Year Citation Rate (OpenAlex) of 0.70 (Q3 quartile) — the average number of citations its recent articles received over a two-year window, computed from OpenAlex open citation data, not the Clarivate (JCR) Impact Factor. It operates a subscription model. It is indexed in the ABDC list (rating B), among the databases we track.
Journal of Applied Statistics Citation Rate 2026 — In Context
Journal of Applied Statistics has a 2025 2-Year Citation Rate (OpenAlex) of 0.70, placing it in the Q3 quartile within the Advanced Statistical Methods and Models research area. This is the average number of citations the journal's recent articles received over a two-year window, computed from OpenAlex open citation data — not the Clarivate (JCR) Journal Impact Factor.
Journal of Applied Statistics operates a subscription-based publishing model — readers access articles through institutional subscriptions or pay-per-view.
Researchers looking to publish in Journal of Applied Statistics should review the journal's submission tips and verify the latest indexing status against Scopus, DOAJ, and Web of Science using our indexing tracker. To compare Journal of Applied Statistics against similar journals in the field, use our journal comparison tool.
Submission Tips for Journal of Applied Statistics
- This journal covers Advanced Statistical Methods and Models, Advanced Statistical Process Monitoring, Statistical Distribution Estimation and Applications. Ensure your manuscript aligns with these scope areas to avoid desk rejection.
How Journal of Applied … Compares
Compared against 18 journals in the same research areas.
| ISSN (Print) | 0266-4763 |
|---|---|
| ISSN (Online) | 1360-0532 |
| Publisher | Taylor & Francis |
| Country | United Kingdom |
| APC / Cost | Inquire with Publisher |
In-depth profile & metrics
Journal of Applied Statistics is published by Taylor & Francis and based in United Kingdom.
In our subject taxonomy, Journal of Applied Statistics is classified under Advanced Statistical Methods and Models, Advanced Statistical Process Monitoring, Statistical Distribution Estimation and Applications and Statistical Methods and Bayesian Inference.
Journal of Applied Statistics is indexed in OpenAlex and carries an ABDC rating of B (2025). OpenAlex tracking provides an open, citable record of its output even where commercial indexing is absent.
Its most recent citation rate stands at 0.695.
Research Areas
Links
Continue on JournalsHub
Put what you just read into practice with these free tools.
Frequently Asked Questions about Journal of Applied Statistics
Live Indexing Status
Updated May 2026Track real-time indexing metrics to ensure this journal meets your academic requirements.
Citation Rate
Historical Trend
Initial data points onlyCitation Rate by Year
| Year | Value | Source |
|---|---|---|
| 2025 | 0.695 | 2-Year Mean Citedness (OpenAlex) |
Metrics are sourced from OpenAlex, DOAJ and Scopus and reflect the latest data we hold. The headline figure is a 2-year citation rate (OpenAlex), not a Clarivate Impact Factor. Always verify against the journal's official site before relying on it. See our Methodology or report a correction.
Compare Journals
Compare Journal of Applied Statistics against similar publications in its field:
Related Journals in Your Field
-
Reliability Engineering & System Safety Elsevier IF 8.42
-
Journal of Econometrics Elsevier BV IF 2.62
-
The Annals of Statistics Institute of Mathematical Statistics IF 2.53
-
Quality & Quantity Springer Science+Business Media IF 1.89
-
Statistics in Medicine Wiley IF 1.55
Explore More Journals
Metadata
Last updated: May 11, 2026
Updated by: openalex_bulk
OpenAlex ID: S167117542
Get weekly updates for Advanced Statistical Methods and Models journals
Free. Monday morning. New citation rates, CFPs, indexing alerts, predatory watch list. One-click unsubscribe.