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Biometrika Template

Write in a clean editor, then format for Biometrika in one click — DocuGuru applies the official Oxford University Press template with author–year references and exports a submission-ready PDF plus the editable LaTeX source. Free to start.

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About the Biometrika format

Biometrika is a peer-reviewed journal published by Oxford University Press, covering Statistical Methods and Inference, Advanced Statistical Methods and Models, Statistical Methods and Bayesian Inference.

PublisherOxford University Press
Reference styleAuthor–year (OUP)
Author–year — (Smith, 2023) in the text
Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', Biometrika, 12(3), pp. 45–58.

Formats any DOI in the closest standard style — Biometrika has no published style definition, so this is an approximation. No sign-up.

Publishes research inStatistical Methods and Inference Advanced Statistical Methods and Models Statistical Methods and Bayesian Inference Bayesian Methods and Mixture Models Optimal Experimental Design Methods
ISSN0006-3444
Citation impact (2-yr)1.87
h-index364
i10-index6,260
Total citations905,863
Article processing charge$3,167
Top institutions publishing hereUniversity College London
Journal websitebiomet.oupjournals.org
You getA submission-ready PDF and the editable LaTeX source — ready to submit.

Papers published in Biometrika per year

82
2014
72
2015
84
2016
84
2017
76
2018
83
2019
107
2020
66
2021
67
2022
76
2023
72
2024
93
2025

Citation impact of Biometrika by publication year

3.3K
2014
3.3K
2015
2.9K
2016
2.4K
2017
2K
2018
1.7K
2019
1.8K
2020
732
2021
959
2022
542
2023
234
2024
123
2025

Citations each year’s papers have accumulated so far — the most recent years are still building up.

Most-cited papers in Biometrika

The central role of the propensity score in observational studies for causal effects

Paul R. Rosenbaum, Donald B. Rubin · 1 Jan 1983

The propensity score is the conditional probability of assignment to a particular treatment given a vector of observed covariates. Both large and small sample theory show that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates. Applications include: (i) matched sampling on the univariate propensity score, which is…

31,128 citations Cite SaveGo to paper →
Longitudinal data analysis using generalized linear models

Kung‐Yee Liang, Scott L. Zeger · 1 Jan 1986

This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence. The estimating equations are derived without specifying the joint distribution of a subject's observations…

18,168 citations Cite SaveGo to paper →
Testing for a unit root in time series regression

Peter C.B. Phillips, Pierre Perrón · 1 Jan 1988

This paper proposes new tests for detecting the presence of a unit root in quite general time series models. Our approach is nonparametric with respect to nuisance parameters and thereby allows for a very wide class of weakly dependent and possibly heterogeneously distributed data. The tests accommodate models with a fitted drift and a time…

18,031 citations Cite SaveGo to paper →
Monte Carlo sampling methods using Markov chains and their applications

W. Keith Hastings · 1 Apr 1970

A generalization of the sampling method introduced by Metropolis et al. (1953) is presented along with an exposition of the relevant theory, techniques of application and methods and difficulties of assessing the error in Monte Carlo estimates. Examples of the methods, including the generation of random orthogonal matrices and potential applications of the methods to…

15,235 citations Cite SaveGo to paper →

Biometrika template — frequently asked questions

How do I write a paper in the Biometrika format?
In DocuGuru you write your manuscript in a normal editor — no LaTeX setup required — and select the Biometrika template. When you export, DocuGuru compiles the paper into the official Oxford University Press format and hands you a submission-ready PDF along with the editable LaTeX source.
What reference style does Biometrika use?
Biometrika uses Author–year (OUP) references, shown as author–year markers such as (Smith, 2023) in the text. DocuGuru formats every in-text citation and the reference list in this exact style automatically. A reference appears like this: Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', Biometrika, 12(3), pp. 45–58.
Do I need to know LaTeX to submit to Biometrika?
No. DocuGuru generates the oup-authoring-template LaTeX class and compiles the PDF for you in the background, so you get a Oxford University Press-ready Biometrika document without writing any LaTeX. If you do want it, the LaTeX source is included in the export.
Can I import an existing draft into the Biometrika template?
Yes. Paste or upload your current manuscript — Word, LaTeX, Markdown, or plain text — and DocuGuru reflows it into the Biometrika format with correct headings, figures, tables, and author–year citations.
Who publishes Biometrika?
Biometrika is a multidisciplinary journal published by Oxford University Press. DocuGuru's Biometrika template matches Oxford University Press's official submission format.
Can I export a submission-ready Biometrika PDF?
Yes — DocuGuru produces a PDF built with the official Biometrika template (the oup-authoring-template class) that is ready to submit to Oxford University Press, together with the matching LaTeX source files.
How much does the Biometrika template cost?
You can start writing in the Biometrika template for free. Exporting the final submission-ready Biometrika PDF and LaTeX source is part of DocuGuru's paid plans — see the app for current pricing.
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