Statistical Considerations for Analyzing Ecological Momentary Assessment Data.


Journal

Journal of speech, language, and hearing research : JSLHR
ISSN: 1558-9102
Titre abrégé: J Speech Lang Hear Res
Pays: United States
ID NLM: 9705610

Informations de publication

Date de publication:
12 01 2022
Historique:
pubmed: 16 12 2021
medline: 25 3 2022
entrez: 15 12 2021
Statut: ppublish

Résumé

The analysis of Ecological Momentary Assessment (EMA) data can be difficult to conceptualize due to the complexity of how the data are collected. The goal of this tutorial is to provide an overview of statistical considerations for analyzing observational data arising from EMA studies. EMA data are collected in a variety of ways, complicating the statistical analysis. We focus on fundamental statistical characteristics of the data and general purpose statistical approaches to analyzing EMA data. We implement those statistical approaches using a recent study involving EMA. The linear or generalized linear mixed-model statistical approach can adequately capture the challenges resulting from EMA collected data if properly set up. Additionally, while sample size depends on both the number of participants and the number of survey responses per participant, having more participants is more important than the number of responses per participant. Using modern statistical methods when analyzing EMA data and adequately considering all of the statistical assumptions being used can lead to interesting and important findings when using EMA. https://doi.org/10.23641/asha.17155961.

Identifiants

pubmed: 34910571
doi: 10.1044/2021_JSLHR-21-00081
pmc: PMC9150728
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

344-360

Subventions

Organisme : NIDCD NIH HHS
ID : F32 DC018980
Pays : United States
Organisme : NIDCD NIH HHS
ID : P50 DC000242
Pays : United States

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Auteurs

Jacob J Oleson (JJ)

Department of Biostatistics, University of Iowa, Iowa City.

Michelle A Jones (MA)

Department of Biostatistics, University of Iowa, Iowa City.

Erik J Jorgensen (EJ)

Department of Communication Sciences and Disorders, University of Iowa, Iowa City.

Yu-Hsiang Wu (YH)

Department of Communication Sciences and Disorders, University of Iowa, Iowa City.

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Classifications MeSH