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Here we provide a selection of academic journal templates for articles and papers which automatically format your manuscripts in the style required for submission to that journal. Thanks to the partnerships we're building within the publishing community, you can also now submit your paper directly to a number of journals and other editorial and review services via the publish menu in the editor.

Template for Service Science

Author template for Service Science (serv) Mirko Janc, Ph.D., INFORMS, mirko.janc@informs.org ver. 0.91, March 2015

Mirko Janc (INFORMS)

LaTeX Template for PeerJ Journal Submissions

This LaTeX template is provided by Overleaf and PeerJ to help make it easier for authors to submit to PeerJ journals. The template contains examples of commonly used LaTeX commands and features to help you get started. You can use this Overleaf template to submit articles to: PeerJ – Life & Environment - a peer-reviewed Open Access journal in the Biological, Medical and Environmental Sciences; PeerJ Computer Science - a peer-reviewed Open Access journal serving the Computational sciences; PeerJ Physical Chemistry - a peer-reviewed Open Access journal in subjects including biophysical chemistry, molecular dynamics, electrochemistry, theoretical and computational chemistry; PeerJ Organic Chemistry - a peer-reviewed Open Access journal in subjects including biochemistry, polymers, green chemistry, photochemistry, and synthetic organic chemistry; PeerJ Inorganic Chemistry - a peer-reviewed Open Access journal in subjects including cluster, organometallic, transition metal, supramolecular and solid-state chemistry; PeerJ Analytical Chemistry - a peer-reviewed Open Access journal in subjects including atomic spectroscopy, omics technologies, separation science, spectroscopic analysis, and surface and structural imaging; Materials Science - a peer-reviewed Open Access journal in subjects including additive manufacturing, bio- and bioinspired materials, smart materials, thin films, gels, alloys, ceramics, colloids, and porous materials. If you have any questions or need any help with the template please get in touch. When your article is complete, use the "Submit to PeerJ" option in Overleaf to send your files to PeerJ. To download a copy of the template files (including the wlpeerj.cls file) for use offline, please click the "Open as Template" button.

Overleaf and PeerJ

Template for Organization Science

Author template for Organization Science (orsc) Mirko Janc, Ph.D., INFORMS, mirko.janc@informs.org ver. 0.95, December 2010

Mirko Janc (INFORMS)

Template for Operations Research

Author template for Operations Research (opre) for articles with e-companion (EC) Mirko Janc, Ph.D., INFORMS, mirko.janc@informs.org ver. 0.96, 11/30/2012

Mirko Janc (INFORMS)

Journal of Computational and Graphical Statistics Example

The very basic LaTeX example/template file that the Journal of Computational and Graphical Statistics provides (as of 2015-09-02)

Journal of Computational and Graphical Statistics

A Bayesian perspective on the Reproducibility Project: Psychology

We revisit the results of the recent Reproducibility Project: Psychology by the Open Science Collaboration. We compute Bayes factors—a quantity that can be used to express comparative evidence for an hypothesis but also for the null hypothesis—for a large subset (N = 72) of the original papers and their corresponding replication attempts. In our computation, we take into account the likely scenario that publication bias had distorted the originally published results. Overall, 75% of studies gave qualitatively similar results in terms of the amount of evidence provided. However, the evidence was often weak (i.e., Bayes factor < 10). The majority of the studies (64%) did not provide strong evidence for either the null or the alternative hypothesis in either the original or the replication, and no replication attempts provided strong evidence in favor of the null. In all cases where the original paper provided strong evidence but the replication did not (15%), the sample size in the replication was smaller than the original. Where the replication provided strong evidence but the original did not (10%), the replication sample size was larger. We conclude that the apparent failure of the Reproducibility Project to replicate many target effects can be adequately explained by overestimation of effect sizes (or overestimation of evidence against the null hypothesis) due to small sample sizes and publication bias in the psychological literature. We further conclude that traditional sample sizes are insufficient and that a more widespread adoption of Bayesian methods is desirable.

Joachim Vandekerckhove