Investigating inter-individual differences in short-term intra-individual variability.

LP Wang, E Hamaker, CS Bergeman - Psychological methods, 2012 - psycnet.apa.org
Psychological methods, 2012psycnet.apa.org
Abstract [Correction Notice: An Erratum for this article was reported in Vol 19 (3) of
Psychological Methods (see record 2014-37187-001). There was a mistake in the code of
the appendix. The correct Appendix is provided in the erratum. Additionally, page 575 of the
article should have stated,“We implemented the multiple-step approach in SAS and the one-
step approach in BUGS (see the Appendix for the BUGS scripts for fitting the proposed
model).] Intra-individual variability over a short period of time may contain important …
Abstract
[Correction Notice: An Erratum for this article was reported in Vol 19 (3) of Psychological Methods (see record 2014-37187-001). There was a mistake in the code of the appendix. The correct Appendix is provided in the erratum. Additionally, page 575 of the article should have stated,“We implemented the multiple-step approach in SAS and the one-step approach in BUGS (see the Appendix for the BUGS scripts for fitting the proposed model).] Intra-individual variability over a short period of time may contain important information about how individuals differ from each other. In this article we begin by discussing diverse indicators for quantifying intra-individual variability and indicate their advantages and disadvantages. Then we propose an alternative method that models inter-individual differences in intra-individual variability by separately considering both the amplitude of fluctuations and temporal dependency in the data. In the proposed model, temporal dependency and amplitude of fluctuations are both included as random effects. Parameter estimation is done with a multiple-step approach using maximum likelihood, or with a recommended 1-step approach using a Bayesian method. The similarities and differences between the proposed method and some existing methods are discussed and investigated using diary study data from older adults. The results from empirical data analysis revealed that temporal dependency and amplitude of fluctuations have different predictability of health outcomes and thus should be modeled and considered separately.(PsycINFO Database Record (c) 2016 APA, all rights reserved)
American Psychological Association
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