LIFESPAN: A Tool for the Computer-Aided Design of Longitudinal Studies
Researchers planning a longitudinal study typically search, more or less informally, a multivariate space of possible study designs that include dimensions such as the hypothesized true variance in change, indicator reliability, the number and spacing of measurement occasions, total study time, and...
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Format: | Article |
Language: | English |
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Frontiers Media S.A.
2015-03-01
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Series: | Frontiers in Psychology |
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Online Access: | http://journal.frontiersin.org/Journal/10.3389/fpsyg.2015.00272/full |
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author | Andreas M Brandmaier Timo evon Oertzen Paolo eGhisletta Paolo eGhisletta Christopher eHertzog Ulman eLindenberger Ulman eLindenberger |
author_facet | Andreas M Brandmaier Timo evon Oertzen Paolo eGhisletta Paolo eGhisletta Christopher eHertzog Ulman eLindenberger Ulman eLindenberger |
author_sort | Andreas M Brandmaier |
collection | DOAJ |
description | Researchers planning a longitudinal study typically search, more or less informally, a multivariate space of possible study designs that include dimensions such as the hypothesized true variance in change, indicator reliability, the number and spacing of measurement occasions, total study time, and sample size. The main search goal is to select a research design that best addresses the guiding questions and hypotheses of the planned study while heeding applicable external conditions and constraints, including time, money, feasibility, and ethical considerations. Because longitudinal study selection ultimately requires optimization under constraints, it is amenable to the general operating principles of optimization in computer-aided design. Based on power equivalence theory (MacCallum et al., 2010; von Oertzen, 2010), we propose a computational framework to promote more systematic searches within the study design space. Starting with an initial design, the proposed framework generates a set of alternative models with equal statistical power for detecting hypothesized effects, and delineates tradeoff relations among relevant parameters, such as total study time and the number of measurement occasions. We present LIFESPAN (Longitudinal Interactive Front End Study Planner) that implements this framework. LIFESPAN boosts the efficiency, breadth, and precision of the search for optimal longitudinal designs. Its initial version, which is freely available at http://www.brandmaier.de/lifespan, is geared towards the power to detect variance in change as specified in a linear latent growth curve model. |
first_indexed | 2024-04-12T17:18:49Z |
format | Article |
id | doaj.art-4159a060563d4149ae7176091fd9c6f5 |
institution | Directory Open Access Journal |
issn | 1664-1078 |
language | English |
last_indexed | 2024-04-12T17:18:49Z |
publishDate | 2015-03-01 |
publisher | Frontiers Media S.A. |
record_format | Article |
series | Frontiers in Psychology |
spelling | doaj.art-4159a060563d4149ae7176091fd9c6f52022-12-22T03:23:32ZengFrontiers Media S.A.Frontiers in Psychology1664-10782015-03-01610.3389/fpsyg.2015.00272134837LIFESPAN: A Tool for the Computer-Aided Design of Longitudinal StudiesAndreas M Brandmaier0Timo evon Oertzen1Paolo eGhisletta2Paolo eGhisletta3Christopher eHertzog4Ulman eLindenberger5Ulman eLindenberger6Max Planck Institute for Human DevelopmentUniversity of VirginiaUniversity of GenevaDistance Learning University SwitzerlandGeorgia Institute of TechnologyMax Planck Institute for Human DevelopmentMax Planck University College London Centre for Computational Psychiatry and Ageing ResearchResearchers planning a longitudinal study typically search, more or less informally, a multivariate space of possible study designs that include dimensions such as the hypothesized true variance in change, indicator reliability, the number and spacing of measurement occasions, total study time, and sample size. The main search goal is to select a research design that best addresses the guiding questions and hypotheses of the planned study while heeding applicable external conditions and constraints, including time, money, feasibility, and ethical considerations. Because longitudinal study selection ultimately requires optimization under constraints, it is amenable to the general operating principles of optimization in computer-aided design. Based on power equivalence theory (MacCallum et al., 2010; von Oertzen, 2010), we propose a computational framework to promote more systematic searches within the study design space. Starting with an initial design, the proposed framework generates a set of alternative models with equal statistical power for detecting hypothesized effects, and delineates tradeoff relations among relevant parameters, such as total study time and the number of measurement occasions. We present LIFESPAN (Longitudinal Interactive Front End Study Planner) that implements this framework. LIFESPAN boosts the efficiency, breadth, and precision of the search for optimal longitudinal designs. Its initial version, which is freely available at http://www.brandmaier.de/lifespan, is geared towards the power to detect variance in change as specified in a linear latent growth curve model.http://journal.frontiersin.org/Journal/10.3389/fpsyg.2015.00272/fullStructural Equation Modelingstatistical poweroptimal designlatent growth curve modelingpower equivalence theoryeffective error |
spellingShingle | Andreas M Brandmaier Timo evon Oertzen Paolo eGhisletta Paolo eGhisletta Christopher eHertzog Ulman eLindenberger Ulman eLindenberger LIFESPAN: A Tool for the Computer-Aided Design of Longitudinal Studies Frontiers in Psychology Structural Equation Modeling statistical power optimal design latent growth curve modeling power equivalence theory effective error |
title | LIFESPAN: A Tool for the Computer-Aided Design of Longitudinal Studies |
title_full | LIFESPAN: A Tool for the Computer-Aided Design of Longitudinal Studies |
title_fullStr | LIFESPAN: A Tool for the Computer-Aided Design of Longitudinal Studies |
title_full_unstemmed | LIFESPAN: A Tool for the Computer-Aided Design of Longitudinal Studies |
title_short | LIFESPAN: A Tool for the Computer-Aided Design of Longitudinal Studies |
title_sort | lifespan a tool for the computer aided design of longitudinal studies |
topic | Structural Equation Modeling statistical power optimal design latent growth curve modeling power equivalence theory effective error |
url | http://journal.frontiersin.org/Journal/10.3389/fpsyg.2015.00272/full |
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