Systematic search of Bayesian statistics in the field of psychotraumatology

Schoot, Rens van de; Schalken, Naomi; Olff, Miranda

doi:10.1080/20008198.2017.1375339

Cited by 26 publications

(21 citation statements)

References 42 publications

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“…Bayesian methods have also increasingly been applied in the field of psychotraumatology, in part due to their ability to handle computationally complex models, sometimes with limited sample sizes (van de Schoot, Schalken, & Olff, 2017). Bayesian statistics have been integrated into some of the other statistical approaches listed here.…”

Section: How New Methods Affect Psychotraumatologymentioning

confidence: 99%

A decennial review of psychotraumatology: what did we learn and where are we going?

Olff

Amstadter

Armour

et al. 2019

European Journal of Psychotraumatology

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On 6 December 2019 we start the 10th year of the European Journal of Psychotraumatogy (EJPT), a full Open Access journal on psychotrauma. This editorial is part of a special issue/ collection celebrating the 10 years anniversary of the journal where we will acknowledge some of our most impactful articles of the past decade (also discussed below and marked with * in the reference list). In this editorial the editors present a decennial review of the field addressing a range of topics that are core to both the journal and to psychotraumatology as a discipline. These include neurobiological developments (genomics, neuroimaging and neuroendocrine research), forms of trauma exposure and impact across the lifespan, mass trauma and early interventions, work-related trauma, trauma in refugee populations, and the potential consequences of trauma such as PTSD or Complex PTSD, but also resilience. We address innovations in psychological, medication (enhanced) and technologyassisted treatments, mediators and moderators like social support and finally how new research methods help us to gain insights in symptom structures or to better predict symptom development or treatment success. We aimed to answer three questions 1. Where did we stand in 2010? 2. What did we learn in the past 10 years? 3. What are our knowledge gaps? We conclude with a number of recommendations concerning top priorities for the future direction of the field of psychotraumatology and correspondingly the journal.

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Section: How New Methods Affect Psychotraumatologymentioning

confidence: 99%

A decennial review of psychotraumatology: what did we learn and where are we going?

Olff

Amstadter

Armour

et al. 2019

European Journal of Psychotraumatology

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“…McNally et al suggest that targeting this symptom in interventions could potentially lead to an improvement in other PTSD symptoms, at least in adult survivors of childhood sexual abuse. For a broader discussion on the application of Bayesian methods to the field of PTSD research, see Bayesian statistics in the field of psychotraumatology (Van de Schoot, Schalken, & Olff, 2017). …”

Section: In This Issuementioning

confidence: 99%

PTSD symptomics: network analyses in the field of psychotraumatology

Armour¹,

Fried

Olff

2017

European Journal of Psychotraumatology

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Recent years have seen increasing attention on posttraumatic stress disorder (PTSD) research. While research has largely focused on the dichotomy between patients diagnosed with mental disorders and healthy controls — in other words, investigations at the level of diagnoses — recent work has focused on psychopathology symptoms. Symptomics research in the area of PTSD has been scarce so far, although several studies have focused on investigating the network structures of PTSD symptoms. The present special issue of EJPT adds to the literature by curating additional PTSD network studies, each looking at a different aspect of PTSD. We hope that this special issue encourages researchers to conceptualize and model PTSD data from a network perspective, which arguably has the potential to inform and improve the efficacy of therapeutic interventions.

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“…Such statements can create the impression that using Bayesian estimation universally solves small sample problems. Although several textbooks on Bayesian estimation stress the important role of prior distributions when Bayesian estimation is used with small samples (e.g., Gelman et al, 2013, p. 88;Kaplan, 2014, p. 291;McElreath, 2016, p. 31), in practice prior distributions are often not carefully chosen, and most empirical researchers rely on default software settings (see e.g., König & van de Schoot, 2017;McNeish, 2016b;van de Schoot, Schalken, & Olff, 2017;van de Schoot, Winter, et al, 2017). Popular software programs, such as: Mplus (L. K. Muthén & Muthén, 2017); SPSS (IBM Corp., 2017); JASP (JASP team, 2018); or the R package blavaan (Merkle & Rosseel, 2018), offer Bayesian estimation with diffuse default prior distributions.…”

mentioning

confidence: 99%

Bayesian Versus Frequentist Estimation for Structural Equation Models in Small Sample Contexts: A Systematic Review

Smid

McNeish

Miočević

et al. 2019

Structural Equation Modeling: A Multidisciplinary Journal

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168

137

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In small sample contexts, Bayesian estimation is often suggested as a viable alternative to frequentist estimation, such as maximum likelihood estimation. Our systematic literature review is the first study aggregating information from numerous simulation studies to present an overview of the performance of Bayesian and frequentist estimation for structural equation models with small sample sizes. We conclude that with small samples, the use of Bayesian estimation with diffuse default priors can result in severely biased estimatesthe levels of bias are often even higher than when frequentist methods are used. This bias can only be decreased by incorporating prior information. We therefore recommend against naively using Bayesian estimation when samples are small, and encourage researchers to make well-considered decisions about all priors. For this purpose, we provide recommendations on how to construct thoughtful priors.

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Systematic search of Bayesian statistics in the field of psychotraumatology

Cited by 26 publications

References 42 publications

A decennial review of psychotraumatology: what did we learn and where are we going?

A decennial review of psychotraumatology: what did we learn and where are we going?

PTSD symptomics: network analyses in the field of psychotraumatology

Bayesian Versus Frequentist Estimation for Structural Equation Models in Small Sample Contexts: A Systematic Review

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