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Planned missingness in intensive longitudinal studies: Extensions and comparisons of multiform designs.

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Τίτλος: Planned missingness in intensive longitudinal studies: Extensions and comparisons of multiform designs.
Συγγραφείς: Chen Y; Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education, Faculty of Psychology, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Hai Dian District, Beijing, 100875, China. yilanchen@mail.bnu.edu.cn., Liu H; Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education, Faculty of Psychology, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Hai Dian District, Beijing, 100875, China. hyliu@bnu.edu.cn.; Research Center for Capacity Building in Educational Assessment and Evaluation (Beijing Higher Education Innovation Center for Philosophy and Social Sciences), Beijing, China. hyliu@bnu.edu.cn.
Πηγή: Behavior research methods [Behav Res Methods] 2026 Jul 01; Vol. 58 (8). Date of Electronic Publication: 2026 Jul 01.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Springer Country of Publication: United States NLM ID: 101244316 Publication Model: Electronic Cited Medium: Internet ISSN: 1554-3528 (Electronic) Linking ISSN: 1554351X NLM ISO Abbreviation: Behav Res Methods Subsets: MEDLINE
Imprint Name(s): Publication: 2010- : New York : Springer
Original Publication: Austin, Tex. : Psychonomic Society, c2005-
Ιατρικοί όροι (MeSH): Data Collection*/methods , Research Design* , Models, Statistical*, Humans ; Longitudinal Studies ; Data Interpretation, Statistical ; Computer Simulation ; Sample Size
Περίληψη: Technological advances in data collection have made intensive longitudinal studies (ILSs) increasingly feasible. However, conducting such studies often leads to increased participant burden due to the high frequency of measurements, resulting in nonresponse and a consequent reduction in data quantity and quality. Previous studies have shown that planned missingness designs can help optimize data collection. In this paper, we extend two multiform designs commonly used in planned missingness research and propose a flexible alternative involving completely random sampling. These designs are better tailored to ILSs by varying item subset combinations across measurement occasions for each participant. Specifically, we examined (1) the anchor test design, where a core subset is administered to all participants across all occasions; (2) the matrix sampling design, where subset combinations rotate systematically; and (3) the random sampling design, where subset combinations are randomly assigned at each occasion. We conducted two simulation studies to evaluate the performance of these designs within the dynamic structural equation modeling (DSEM) framework across varying key model parameters, sample sizes, numbers of time points, and planned missingness proportions. An empirical example is also provided to demonstrate the potential of multiform designs in ILSs. Results indicate that these multiform designs can yield unbiased parameter point estimates with acceptable credible interval coverage rates, while maintaining sufficient statistical power. Therefore, the extended and proposed multiform designs enable researchers to reduce both the costs and participant burden while still obtaining adequate data to capture characteristics in the dynamic process.
(© 2026. The Psychonomic Society, Inc.)
Competing Interests: Declarations. Ethics approval: Not applicable. Consent to participate: Not applicable. Consent for publication: All authors approve the final version of the article. Conflict of interest: There are no conflicts of interest to disclose.
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Grant Information: 32471145 National Natural Science Foundation of China
Contributed Indexing: Keywords: Dynamic structural equation model; Intensive longitudinal data; Multiform design; Planned missingness design
Entry Date(s): Date Created: 20260702 Date Completed: 20260702 Latest Revision: 20260729
Update Code: 20260729
DOI: 10.3758/s13428-026-03035-8
PMID: 42390678
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:1554-3528
DOI:10.3758/s13428-026-03035-8