Evidence map›Paper›PMID 39850466›Full record

ArticleAdvances in methods and practices in psychological science

A Tutorial on Analyzing Ecological Momentary Assessment Data in Psychological Research With Bayesian (Generalized) Mixed-Effects Models.

Jonas Dora, Connor J McCabe, Caspar J van Lissa, Katie Witkiewitz, Kevin M King

Abstract read
In one paragraph

Article in Advances in methods and practices in psychological science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Measuring Coping Strategies in Daily Life: A Systematic Review of Experience Sampling Methodology and Daily Diary Studies.Stress and health : journal of the International Society for the Investigation of Stress · 2026
    Pooled it
  2. Article
  3. Article
  4. UPPS-P Impulsivity, Momentary Affect, and Gambling: An Experience Sampling Method Study.Journal of psychopathology and behavioral assessment · 2026
    Article
  5. Article
  6. Daily self-control demands and loss of control over drinking: The moderating role of trait impulsivity and peer exposure.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2026
    Article
  7. Alcohol and cannabis use predicted by affect-urgency interactions in everyday life.Clinical psychological science : a journal of the Association for Psychological Science · 2026
    Article
  8. Article
  9. Utilizing ecological momentary assessment in nursing research.Women's health nursing (Seoul, Korea) · 2024
    Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jonas DoraDepartment of Psychology, University of Washington, Seattle, Washington.ORCID 0000-0003-0651-8479
Connor J McCabeDepartment of Psychology, University of Washington, Seattle, Washington.
Caspar J van LissaDepartment of Methodology & Statistics, Tilburg University, Tilberg, the Netherlands.
Katie WitkiewitzCenter on Alcohol, Substance Use, and Addictions, University of New Mexico, Albuquerque, New Mexico.ORCID 0000-0002-1086-3067
Kevin M KingDepartment of Psychology, University of Washington, Seattle, Washington.ORCID 0000-0001-8358-9946

Funding

Ecological Momentary Assessment of Negative Urgency's Effects on Alcohol and Marijuana MisuseR01DA047247 · NIDA · UNIVERSITY OF WASHINGTON · PI KING, KEVIN MICHAEL · 2019 to 2023
$2.9M
Exploring affect-motivated alcohol use as a value-based decision-making processK99AA030591 · NIAAA · UNIVERSITY OF WASHINGTON · PI DORA, JONAS · 2023 to 2024
$349k
NIAAA NIH HHS K99 AA030591NIDA NIH HHS R01 DA047247
6 · The paper itself

Abstract

In this tutorial, we introduce the reader to analyzing ecological momentary assessment (EMA) data as applied in psychological sciences with the use of Bayesian (generalized) linear mixed-effects models. We discuss practical advantages of the Bayesian approach over frequentist methods and conceptual differences. We demonstrate how Bayesian statistics can help EMA researchers to (a) incorporate prior knowledge and beliefs in analyses, (b) fit models with a large variety of outcome distributions that reflect likely data-generating processes, (c) quantify the uncertainty of effect-size estimates, and (d) quantify the evidence for or against an informative hypothesis. We present a workflow for Bayesian analyses and provide illustrative examples based on EMA data, which we analyze using (generalized) linear mixed-effects models to test whether daily self-control demands predict three different alcohol outcomes. All examples are reproducible, and data and code are available at https://osf.io/rh2sw/. Having worked through this tutorial, readers should be able to adopt a Bayesian workflow to their own analysis of EMA data.

Indexed as

bayesian statisticsbrmsecological momentary assessmentmixed-effects modelingtutorial

Identifiers

PMID39850466
PMCPMC11756902

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.