ArticleFrontiers in psychology2015
LIFESPAN: A tool for the computer-aided design of longitudinal studies.
Article in Frontiers in psychology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Coupled cognitive changes in adulthood: A meta-analysis.Psychological bulletin · 2019Pooled it
- Reliability of structural brain change in cognitively healthy adult samples.bioRxiv : the preprint server for biology · 2025Article
- Reliability of structural brain change in cognitively healthy adult samples.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Estimating statistical power for structural equation models in developmental cognitive science: A tutorial in R : Power simulation for SEMs.Behavior research methods · 2024Article
- Longitudinal stability of cortical grey matter measures varies across brain regions, imaging metrics, and testing sites in the ABCD study.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Power contours: Optimising sample size and precision in experimental psychology and human neuroscience.Psychological methods · 2021Article
- How to Arrange Follow-Up Time-Intervals for Longitudinal Brain MRI Studies in Neurodegenerative Diseases.Frontiers in neuroscience · 2021Article
- Bayesian power equivalence in latent growth curve models.The British journal of mathematical and statistical psychology · 2020Article
- A COVID-19 descriptive study of life after lockdown in Wuhan, China.Royal Society open science · 2020Article
- Optimal planned missing data design for linear latent growth curve models.Behavior research methods · 2020Article
- Brain structure and cognitive ability in healthy aging: a review on longitudinal correlated change.Reviews in the neurosciences · 2019Review
- Cortical thickness lateralization and its relation to language abilities in children.Developmental cognitive neuroscience · 2019Article
- Developmental cognitive neuroscience using latent change score models: A tutorial and applications.Developmental cognitive neuroscience · 2018Review
- Assessing reliability in neuroimaging research through intra-class effect decomposition (ICED).eLife · 2018Article
- Precision, Reliability, and Effect Size of Slope Variance in Latent Growth Curve Models: Implications for Statistical Power Analysis.Frontiers in psychology · 2018Article
- The challenge of measuring intra-individual change in fatigue during cancer treatment.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2017Article
- Prospective Validation of the Decalogue, a Set of Doctor-Patient Communication Recommendations to Improve Patient Illness Experience and Mood States within a Hospital Cardiologic Ambulatory Setting.BioMed research international · 2017Article
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5 authors.
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Abstract
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 to detect hypothesized effects, and delineates trade-off relations among relevant parameters, such as total study time and the number of measurement occasions. We present LIFESPAN (Longitudinal Interactive Front End Study Planner), which 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 toward the power to detect variance in change as specified in a linear latent growth curve model.
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