IDEAS home Printed from https://ideas.repec.org/a/plo/pmen00/0000253.html
   My bibliography  Save this article

A tutorial on the what, why, and how of Bayesian analysis: Estimating mood and anxiety disorder prevalence using a Canadian data linkage study

Author

Listed:
  • Myanca Rodrigues
  • Jordan Edwards
  • Tea Rosic
  • Yanchen Wang
  • Jhalok Ronjan Talukdar
  • Saifur R Chowdhury
  • Sameer Parpia
  • Glenda Babe
  • Claire de Oliveira
  • Richard Perez
  • Zainab Samaan
  • Lehana Thabane

Abstract

Bayesian analyses offer a robust framework for integrating data from multiple sources to better inform population-level estimates of disease prevalence. This methodological approach is particularly suited to instances where data from observational studies is linked to administrative health records, with the capacity to advance our understanding of psychiatric disorders. The objective of our paper was to provide an introductory overview and tutorial on Bayesian analysis for primary observational studies in mental health research. We provided: (i) an overview of Bayesian statistics, (ii) the utility of Bayesian methods for psychiatric epidemiology, (iii) a tutorial example of a Bayesian approach to estimating the prevalence of mood and/or anxiety disorders in observational research, and (iv) suggestions for reporting Bayesian analyses in health research.Author summary: Mental health conditions, like anxiety and depression, are common and can greatly impact people’s lives. Knowing how many people are affected is important for planning healthcare services and improving treatment. However, combining information from different sources, such as health surveys and medical records, may be challenging with traditional methods.

Suggested Citation

  • Myanca Rodrigues & Jordan Edwards & Tea Rosic & Yanchen Wang & Jhalok Ronjan Talukdar & Saifur R Chowdhury & Sameer Parpia & Glenda Babe & Claire de Oliveira & Richard Perez & Zainab Samaan & Lehana T, 2025. "A tutorial on the what, why, and how of Bayesian analysis: Estimating mood and anxiety disorder prevalence using a Canadian data linkage study," PLOS Mental Health, Public Library of Science, vol. 2(2), pages 1-25, February.
    • Handle: RePEc:plo:pmen00:0000253
    DOI: 10.1371/journal.pmen.0000253
    as

    Download full text from publisher

    File URL: https://journals.plos.org/mentalhealth/article?id=10.1371/journal.pmen.0000253
    Download Restriction: no
    File URL: https://journals.plos.org/mentalhealth/article/file?id=10.1371/journal.pmen.0000253&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pmen.0000253?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Denes Szucs & John P A Ioannidis, 2017. "Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature," PLOS Biology, Public Library of Science, vol. 15(3), pages 1-18, March.
    2. Niels Keiding, 1991. "Age‐Specific Incidence and Prevalence: A Statistical Perspective," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 154(3), pages 371-396, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kleber Neves & Pedro B Tan & Olavo B Amaral, 2022. "Are most published research findings false in a continuous universe?," PLOS ONE, Public Library of Science, vol. 17(12), pages 1-18, December.
    2. Limin X. Clegg & Mitchell H. Gail & Eric J. Feuer, 2002. "Estimating the Variance of Disease-Prevalence Estimates from Population-Based Registries," Biometrics, The International Biometric Society, vol. 58(3), pages 684-688, September.
    3. Rinne, Sonja, 2024. "Estimating the merit-order effect using coarsened exact matching: Reconciling theory with the empirical results to improve policy implications," Energy Policy, Elsevier, vol. 185(C).
    4. Andreas Schneck, 2023. "Are most published research findings false? Trends in statistical power, publication selection bias, and the false discovery rate in psychology (1975–2017)," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-18, October.
    5. repec:osf:osfxxx:7dc6a_v1 is not listed on IDEAS
    6. Oliver Braganza, 2020. "A simple model suggesting economically rational sample-size choice drives irreproducibility," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-19, March.
    7. Mitchell H. Gail & Larry Kessler & Douglas Midthune & Steven Scoppa, 1999. "Two Approaches for Estimating Disease Prevalence from Population-Based Registries of Incidence and Total Mortality," Biometrics, The International Biometric Society, vol. 55(4), pages 1137-1144, December.
    8. Sungwook Kim & Michael P. Fay & Michael A. Proschan, 2021. "Valid and approximately valid confidence intervals for current status data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(3), pages 438-452, July.
    9. Chantal Guihenneuc-Jouyaux & Sylvia Richardson & Ira M. Longini Jr., 2000. "Modeling Markers of Disease Progression by a Hidden Markov Process: Application to Characterizing CD4 Cell Decline," Biometrics, The International Biometric Society, vol. 56(3), pages 733-741, September.
    10. repec:plo:pone00:0044377 is not listed on IDEAS
    11. Kathryn N. Vasilaky & J. Michelle Brock, 2020. "Power(ful) guidelines for experimental economists," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 6(2), pages 189-212, December.
    12. Marcia C Castro & Mathieu Maheu-Giroux & Christinah Chiyaka & Burton H Singer, 2016. "Malaria Incidence Rates from Time Series of 2-Wave Panel Surveys," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-26, August.
    13. Uddin, Shahadat & Khan, Arif & Lu, Haohui, 2023. "Impact of COVID-19 on Journal Impact Factor," Journal of Informetrics, Elsevier, vol. 17(4).
    14. Kathryn Vasilaky & Sofía Martínez Sáenz & Radost Stanimirova & Daniel Osgood, 2020. "Perceptions of Farm Size Heterogeneity and Demand for Group Index Insurance," Games, MDPI, vol. 11(1), pages 1-21, March.
    15. repec:plo:pone00:0205225 is not listed on IDEAS
    16. Livingston, Jeffrey A. & Rasulmukhamedov, Rustam, 2023. "On the Interpretation of Giving in Dictator Games When the Recipient is a Charity," Journal of Economic Behavior & Organization, Elsevier, vol. 208(C), pages 275-285.
    17. Filip Melinscak & Dominik R Bach, 2020. "Computational optimization of associative learning experiments," PLOS Computational Biology, Public Library of Science, vol. 16(1), pages 1-23, January.
    18. Auer, Tobias & Ulasik, Maria & Holzmeister, Felix, 2024. "A Comment on "Motivated Errors" by Exley and Kessler (2024)," I4R Discussion Paper Series 161, The Institute for Replication (I4R).
    19. Augusteijn, Hilde Elisabeth Maria & Wicherts, Jelte M. & Sijtsma, Klaas & van Assen, Marcel A. L. M., 2023. "Quality assessment of scientific manuscripts in peer review and education," OSF Preprints 7dc6a, Center for Open Science.
    20. AsleBagh, Pegah & Bonyadi Naeini, Ali & Moeeni, MohammadReza, 2024. "Investigating the effect of three different factors including experience, personality and color on the decision-making process in stock markets using EEG," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 109(C).
    21. Esteban Morales & Erin C McKiernan & Meredith T Niles & Lesley Schimanski & Juan Pablo Alperin, 2021. "How faculty define quality, prestige, and impact of academic journals," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-13, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pmen00:0000253. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: mentalhealth (email available below). General contact details of provider: https://journals.plos.org/mentalhealth/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.