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• W4386090410 abstract "In psychology, the use of portable technology and wearable devices to ease participant burden in data collection is on the rise. This creates increased interest in collecting real-time or near real-time data from individuals within their natural environments. As a result, vast amounts of observational time series data are generated. Often, motivation for collecting this data hinges on understanding within-person processes that underlie psychological phenomena. Motivated by the body of Dr. Peter Molenaar's life work calling for analytical approaches that consider potential heterogeneity and non-ergodicity, the focus of this paper is on using idiographic analyses to generate population inferences for within-person processes. Meta-analysis techniques using one-stage and two-stage random effects meta-analysis as implemented in single-case experimental designs are presented. The case for preferring a two-stage approach for meta-analysis of single-subject observational time series data is made and demonstrated using an empirical example. This provides a novel implementation of the methodology as prior implementations focus on applications to short time series with experimental designs. Inspired by Dr. Molenaar's work, we describe how an approach, two-stage random effects meta-analysis (2SRE-MA), aligns with recent calls to consider idiographic approaches when making population-level inferences regarding within-person processes." @default.
• W4386090410 created "2023-08-24" @default.
• W4386090410 creator A5002614287 @default.
• W4386090410 creator A5006142227 @default.
• W4386090410 date "2023-08-23" @default.
• W4386090410 modified "2023-09-27" @default.
• W4386090410 title "From the Individual to the Group: Using Idiographic Analyses and Two-Stage Random Effects Meta-Analysis to Obtain Population Level Inferences for within-Person Processes" @default.
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• W4386090410 doi "https://doi.org/10.1080/00273171.2023.2229310" @default.
• W4386090410 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37611153" @default.

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