Research

Meta-research and reproducibility

Meta-research aims to study and improve research practices and processes. I am specifically interested in developing methods to diagnose and address issues related to the reproducibility, transparency and overall quality of published research. Ongoing work in this area of research includes developing methodology for assessing and designing replication studies, improving reproducibility and identifying issues related to credibility. I highlight specific research projects below.

  • improving Reproducibility In SciencE (iRISE) – This project is funded through the Horizon Europe WIDERA call Increasing the Reproducibility of Scientific Results (WIDERA-2022-ERA-01-41). I lead the theory work package of the project. The goal of iRISE is to deepen our understanding of reproducibility drivers and to evaluate the effectiveness of interventions aimed at improving reproducibility.

    NoteKey publications

    C. J. Huang, S. Pawel, K. E. Wever, B. V. Ineichen and R. Heyard (2026). Evaluating the applicability of replication success metrics in animal-to-human translation: A simulation study. eLife. https://doi.org/10.7554/eLife.109853.1

    R. Heyard, S. Pawel, J. Frese, B. Voelkl, H. Würbel, S. McCann, L. Held, K. E. Wever, H. Hartmann, L. Townsin and S. Zellers (2025) A scoping review on metrics to quantify reproducibility: a multitude of questions leads to a multitude of metrics. Royal Society Open Science. https://doi.org/10.1098/rsos.242076

  • INSPECT: Identifying Non-obvious Signals in Protocols for Early Credibility Threats – This project will examine whether it is possible to identify potential red flags for questionable research practices (QRPs) and potential scientific misconduct from clinical trial protocols or statistical analysis plans. I am the PI of this project, which is further described here.

    NoteProtocol for our rapid review

    A. Rojas Mora, P.M. Degen, L. Held, U. Held and R. Heyard (2025) Identifying questionable research practices and types of misconduct during the planning phase of clinical trials: a rapid review. OSF. https://osf.io/29b3f

  • CORTRE – COmplete Reporting for Transparent Reproducibility Efforts – This project aims to develop a consensus-based reporting guideline for large-scale “meta-studies” that investigate reproducibility, replicability, robustness, generalisability, or related concepts. More information is available on the project website.

    NoteKey publications

    R. Heyard, M.-M. Pittelkow, P. Silverstein, O. B. Amaral, S. Gordon, M. Wasylewski,and F. Molo (2026). COmplete Reporting for Transparent Reproducibility Efforts (CORTRE): a reporting guideline [Stage 1 Registered Report]. In principle acceptance of Version 2 by Peer Community in Registered Reports. https://osf.io/n4k58

  • DREAMR / Table 1 project – With this project, we aim to propose a standard sample characteristics table structure for studies performed on research papers (i.e., meta-research).

    NoteKey publications

    S. Zellers, R. Heyard, M. Salholz-Hillel, S. Smith, K. Thomson, E. Sena, K. E. Wever, K. Hair and T. Weissgerber (2025). Building a sample characteristics table for studies on peer-reviewed publications: Rationale and pipeline development. MetaArxiv. https://doi.org/10.31222/osf.io/2yhux_v2

  • Analysis of Replication Studies – Research on methodologies to assess replication success and design replication studies.

    NoteKey publications

    S. Pawel, R. Heyard, C. Micheloud and L. Held (2024). Replication of “null results” – Absence of evidence or evidence of absence? eLife. https://doi.org/10.7554/eLife.92311.3.sa0

    F. Freuli, L. Held and R. Heyard (2023). Replication Success Under Questionable Research Practices — a Simulation Study. Statistical Science. https://doi.org/10.1214/23-STS904

  • Explaining variation and heterogeneity in replication projects and in real world evidence emulations

    NoteKey publications

    R. Heyard and L. Held (2024). Meta-regression to explain shrinkage and heterogeneity in large-scale replication projects. To appear in PLOS ONE. https://doi.org/10.31222/osf.io/e9nw2

    J. Köppe, C. Micheloud, S. Erdmann, R. Heyard and L. Held (2024) Assessing the replicability of RCTs in RWE emulations. BMC Medical Research Methodology. https://doi.org/10.1186/s12874-025-02589-z

    R. Heyard, L. Held, S. Schneeweiss and S. V. Wang (2024). Design differences and variation in results between randomised trials and non-randomised emulations: meta-analysis of RCT-DUPLICATE data. BMJ Medicine. https://doi.org/10.1136/bmjmed-2023-000709

Decision-making under uncertainty and funding lotteries

While working at Swiss National Science Foundation, I (co-)developed a Bayesian ranking (BR) methodology to support decision-making in contexts where limited resources must be allocated under uncertainty. The method is useful not only in the context of decision-making in research funding, but also for example when prioritising drugs or components for further development. More recently, I became interested in the “degrees of freedom” funders have when designing a funding call, which led to a collaborative project with T. Feliciani (see below).

NoteKey publications and outputs

R. Heyard, H. Wnfried Ramirez, B. Jann, D. Rohner, L. Held, and M. Egger (2026). Lottery funding and academic career outcomes: a randomized natural experiment at the Swiss National Science Foundation. Zenodo. https://doi.org/10.5281/zenodo.23189200

R. Heyard, G. Chan and T. Feliciani (2026). Decision-making processes for research funding – a review protocol. Protocol on Zenodo. https://doi.org/10.5281/zenodo.19133106

R. Heyard, D. Pina, I. Buljan and A. Marusic (2025). Assessing the potential of a Bayesian ranking as an alternative to consensus meetings for decision making in research funding: A Case Study of Marie Skłodowska-Curie Actions. PLOS ONE. https://doi.org/10.1371/journal.pone.0317772

R. Heyard (2023). ERforResearch: Expected Rank for Research Evaluation. R package version 4.0.0. https://github.com/snsf-data/ERforResearch

R. Heyard, M. Ott, G. Salanti and M. Egger (2022) Rethinking the Funding Line at the Swiss National Science Foundation: Bayesian Ranking and Lottery. Statistics and Public Policy. https://doi.org/10.1080/2330443X.2022.2086190

M. Bieri, K. Roser, R. Heyard and M. Egger (2020). Face-to-face panel meetings versus remote evaluation of fellowship applications: simulation study at the Swiss National Science Foundation. BMJ Open. https://doi.org/10.1136/bmjopen-2020-047386

Research assessment

I am interested in evaluating the quality, credibility, and utility of research, either by aggregating evidence across studies, methods or evidence types, or by assessing the strength or the quality of (a body of) research. Applying this to the researcher-level, novel methodology in this space could inform responsible research assessment that rewards openness, collaboration and methodological rigour. In this space, I am currently invested in the CoARA working group on reponsible Indicators and Metrics. I also lead a working group on Research Assessment and Incentives for the Swiss Reproducibility Network.

NoteKey publications and outputs

D. Crepaldi, R. Heyard, K. A. Nawrot, F. D. Sch"{o}nbrodt et al (2025) On the responsible use of metrics and indicators in research assessment. Preprint. 10.31222/osf.io/9cdns_v1

R. Heyard, E. Furrer, L. Held, H. Würbel, E. Vergauwe and M. Ochsner (2024) Towards a comprehensive and community-accepted SNSF research output list. https://osf.io/vgs4b

E. Furrer, M. Ochsner, R. Heyard, C. Priboi, E. Vergauwe, H. Würbel and L. Held (2025). SIRRO Recommendations Open Science in Research Evaluation. https://osf.io/gya3s

N. Turoman, R. Heyard, S. Schwab, E. Furrer, E. Vergauwe and L. Held (2023). Using an expert survey and user feedback to construct PRECHECK: A checklist to evaluate preprints on COVID-19 and beyond. F1000 Research. https://doi.org/10.12688/f1000research.129814.3

R. Heyard, T. Philipp and H. Hottenrott (2021). Imaginary carrot or effective fertiliser? A rejoinder on funding and productivity. Scientometrics. https://doi.org/10.1007/s11192-021-04130-7

R. Heyard and H. Hottenrott (2021). The value of research funding for knowledge creation and dissemination: A study of SNSF Research Grants. Humanities and Social Sciences Communications. https://doi.org/10.1057/s41599-021-00891-x