The OnlineOpen publishing option in Wiley Biostatistics journals allows you to access select content without a subscription. When you see the open sign next to an article you can read this for free.
Consider making your next article Open Access
Benefits for Authors
As an author, do you search for the easiest way to make your research instantly open and accessible to millions of readers? Why not consider Wiley OnlineOpen when publishing your next article?
What is Wiley OnlineOpen?
If you are an author and you want to make your article freely available on publication, or your funding agency requires you to archive the final version of your article, then OnlineOpen is an easy option available to you in some of the best journals in the world. Authors of primary research articles (including short communications) and review articles can take advantage of OnlineOpen.
Does it mean it is free for all to read?
Yes, if you choose to publish your articles OnlineOpen then you can post the final, published PDF of their article on a website, institutional repository or other free public server, immediately on publication.
How does it work? Will my article get preferential treatment?
All OnlineOpen articles are treated in the same way as any other article. Your article will go through the journal's peer-review process and will be accepted or rejected based on the article's own merit.
Once accepted for publication, your articles are posted online on Wiley Online Library. The articles are archived for perpetuity and are registered at relevant Abstracting and Indexing Services and at CrossRef. Read more here.
As an author, you pay a fee to ensure that the article is made available to non-subscribers upon publication via Wiley Online Library, as well as deposited in your preferred archive. Sometimes, your funding agency or institution pays the publication charge.
Do you have resources to support authors?
Read some of the existing OnlineOpen papers published in our Biostatistics journals. No subscription required.
Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications
Alexandra C. Graf, Peter Bauer, Ekkehard Glimm andFranz Koenig
Estimating peer effects in longitudinal dyadic data using instrumental variables
James O'Malley, Felix Elwert, J. Niels Rosenquist, Alan M. Zaslavsky and Nicholas A. Christakis
Biometrics: Journal of the International Biometric Society
HAC robust trend comparisons among climate series with possible level shifts
Ross R. McKitrick and Timothy J. Vogelsang
Review of methodological issues in cost-effectiveness analyses relating to injecting drug users, and case-study illustrations
Simon R. White, Sheila M. Bird and Richard Grieve
Journal of the Royal Statistical Society: Series A (Statistics in Society)
Variable importance in matched case–control studies in settings of high dimensional data
Raji Balasubramanian, E. Andres Houseman, Brent A. Coull, Michael H. Lev, Lee H. Schwamm and Rebecca A. Betensky
Journal of the Royal Statistical Society: Series C (Applied Statistics)
Data-driven treatment selection for seamless phase II/III trials incorporating early-outcome data
Cornelia Ursula Kunz, Tim Friede, Nick Parsons, Susan Todd and Nigel Stallard
A multivariate model for the meta-analysis of study level survival data at multiple times
Dan Jackson, Katie Rollins and Patrick Coughlin
Research Synthesis Methods
Estimating the proportions in a mixed sample using transcriptomics
Bertrand Clarke and Jennifer Clarke
Relaxing the independent censoring assumption in the Cox proportional hazards model using multiple imputation
Dan Jackson, Ian R. White, Shaun Seaman, Hannah Evans, Kathy Baisley and James Carpenter
Statistics in Medicine
Community detection in large-scale networks: a survey and empirical evaluation
Steve Harenberg, Gonzalo Bello, L. Gjeltema, Stephen Ranshous, Jitendra Harlalka, Ramona Seay, Kanchana Padmanabhan, and Nagiza Samatova
Wiley Interdisciplinary Reviews: Computational Statistics