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Gepubliceerd in: Quality of Life Research 1/2008

01-02-2008

Analyzing growth and change: latent variable growth curve modeling with an application to clinical trials

Auteur: Donald E. Stull

Gepubliceerd in: Quality of Life Research | Uitgave 1/2008

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Abstract

Objective

Typical methods of analyzing data from clinical trials have shortcomings, notably comparisons of group means, use of change scores from pre- and post-treatment assessments, ignoring intervening assessments, and focusing on direct effects of treatment. A comparison of group means disregards the likelihood that individuals have different trajectories of change. Moreover, change scores ignore intervening assessments that may provide useful information about change. This paper compares results from traditional regression-based methods for analyzing data from a clinical trial (e.g., regression with change scores) with those of latent growth curve modeling (LGM).

Methods

LGM is a method that uses structural equation modeling techniques to model individual change, assess treatment effects and the relationship among multiple outcomes simultaneously, and model measurement error. The consequence is more precise parameter estimates while using data from all available time points.

Results

Results demonstrate that LGM can yield stronger parameter estimates than the traditional regression-based approach and explain more variance in the outcome. In trials where there is a true effect, but it is non-significant or marginally significant using the traditional methods, LGM may provide evidence of this effect.

Conclusions

Analysts are encouraged to consider LGM as an additional and informative tool for analyzing clinical trial or other longitudinal data.
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Metagegevens
Titel
Analyzing growth and change: latent variable growth curve modeling with an application to clinical trials
Auteur
Donald E. Stull
Publicatiedatum
01-02-2008
Uitgeverij
Springer Netherlands
Gepubliceerd in
Quality of Life Research / Uitgave 1/2008
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-007-9290-5

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