The Karma system is currently undergoing maintenance (Monday, January 29, 2018).
The maintenance period has been extended to 8PM EST.

Karma Credits will not be available for redeeming during maintenance.
Back to Annoucements Index

Special Issue: Analysis of Randomized Controlled Trials in a Bayesian Framework

The Journal of Medical Internet Research (JMIR) is inviting submissions for a special issue of the journal that will be dedicated to the analysis of randomized controlled trials (RCTs) in a Bayesian framework.

The reoccurring debate regarding the use of P values has again flared up, much due to the general warning from the American Statistical Association, the attention it has been given due to Regina Nuzzo's view paper in Nature, and the banning of P values from the journal Basic and Applied Social Psychology. Change is coming, albeit slow, and it is going to require a re-education and possibly much debate before a new consensus is found on how to deal with evidence from scientific studies.

One approach that has been proposed is to use a Bayesian framework to analyze data from trials. Evidence would then be considered a continuous measure and would not be dichotomized into significant or non-significant. Researchers conducting a trial would then be responsible for assessing the evidence collected using a holistic view, taking into consideration trial design, potential biases, costs involved in rolling out the intervention, risks to patients, results from previous studies, and any other relevant factors.

We are therefore seeking short papers in which authors re-analyze their RCT data using a Bayesian framework. We are also offering the possibility for authors to upload their data to JMIR Data if they would like support with the analysis (please see details below).

Further information on this process can be found in the following Tutorial: A Gentle Introduction to the Comparison Between Null Hypothesis Testing and Bayesian analysis: Reanalysis of Two Randomized Controlled Trials

Submission of Papers

You are invited to submit a manuscript of no more than 4500 words.

Submitted papers should include a Bayesian analysis of an RCT, presented according to the guideline document for this special issue (Guide for Authors). The RCT should already have been reported through a published original publication using a null hypothesis significance testing approach (the P value approach). All other JMIR guidelines for manuscripts apply.

Manuscripts should be sent through the online system at http://www.jmir.org/author.

In submission step 1, authors must choose the section “Special Issue: Analysis of Randomized Controlled Trials in a Bayesian Framework (Guest editor: Marcus Bendtsen). See also How do I submit to a theme issue?

All submitted manuscripts will undergo a full peer review process consistent with the usual rigorous editorial criteria for JMIR. Accepted papers will be published in JMIR or may be transferred to JMIR Public Health and Surveillance, JMIR Medical Informatics, JMIR Mental Health, JMIR Human Factors, JMIR Research Protocols, or another JMIR sister journal, according to the focus and impact of the paper. All papers will appear together in an e-collection (theme issue) guest edited by the academics listed below. Papers rejected for the theme issue may still be considered for regular issues.

For this special issue, Article Processing Fees are discounted by 20%.

JMIR Data

Authors who are interested in contributing to the special issue, but do not have the resources to conduct the Bayesian analysis on their own, can use JMIR Data to access support for their analysis. The editors will conduct the statistical analysis for a selection of projects, and then allow the original authors to interpret and discuss the findings in a submission to the special issue. Read more about JMIR Data here: https://data.jmir.org/announcement/view/138 and submit your dataset here: http://data.jmir.org/author. Please contact the guest editor below once you have submitted your dataset.

Schedule

For authors using JMIR Data:

All authors:

Guest editor

Marcus Bendtsen, Linköping University, marcus.bendtsen@liu.se