Cited by 97Statistical Methods and Bayesian InferenceMental Health Research TopicsPsychometric Methodologies and Testing

Planned missing-data designs in experience-sampling research: Monte Carlo simulations of efficient designs for assessing within-person constructs

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Silvia, Paul J., Kwapil, Thomas R., Walsh, Molly A., Myin-Germeys, Inez·2014·Behavior Research Methods

Abstract

Experience-sampling research involves trade-offs between the number of questions asked per signal, the number of signals per day, and the number of days. By combining planned missing-data designs and multilevel latent variable modeling, we show how to reduce the items per signal without reducing the number of items. After illustrating different designs using real data, we present two Monte Carlo studies that explored the performance of planned missing-data designs across different within-person and between-person sample sizes and across different patterns of response rates. The missing-data designs yielded unbiased parameter estimates but slightly higher standard errors. With realistic sample sizes, even designs with extensive missingness performed well, so these methods are promising additions to an experience-sampler's toolbox.

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Authors
Silvia, P. J., Kwapil, T. R., Walsh, M. A., & Myin-Germeys, I.
Affiliations
University of North Carolina at Greensboro (US)
Corresponding author
Silvia, Paul J.
Venue
Behavior Research Methods
Published
2013-05-25
Volume
46
Issue
1
Pages
41-54
ISSN
  • 1554-351X (ISSN-L)
  • 1554-3528
OpenAlex
W2011681262
Cited by
97
References
53
Citations by year
2026: 10 · 2025: 5 · 2024: 16 · 2023: 9 · 2022: 11 · 2021: 9 · 2020: 11 · 2019: 8 · 2018: 6 · 2017: 4 · 2015: 3 · 2014: 2 · 2013: 2
FWCI
2.05
Type
journal article
Language
en
Open access
Locations
  • Behavior Research Methods (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • NC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro) (submittedVersion)
  • Lirias (KU Leuven) (submittedVersion, other-oa)
  • Research Publications (Maastricht University) (submittedVersion)
Funders
National Institute of Mental Health (R15MH079374)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Keywords
planned missing data, response rate, design efficiency, item reduction, within-person variability, between-person variation
MeSH terms
Data Interpretation, Statistical, Humans, Monte Carlo Method, Research Design, Likelihood Functions, Sample Size, Behavioral Research

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