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• W2313005306 abstract "This study demonstrates how to use a shared parameter mixture model (SPMM) in longitudinal psychotherapy studies to accommodate missingness that is due to a correlation between rate of improvement and termination of therapy. Traditional growth models assume that such a relationship does not exist (i.e., assume that data are missing at random) and produce biased results if this assumption is incorrect.We used longitudinal data from 4,676 patients enrolled in a naturalistic study of psychotherapy to compare results from a latent growth model and an SPMM.In this data set, estimates of the rate of improvement during therapy differed by 6.50%-6.66% across the two models, indicating that participants with steeper trajectories left psychotherapy earliest, thereby potentially biasing inference for the slope in the latent growth model.We conclude that reported estimates of change during therapy may be underestimated in naturalistic studies of therapy in which participants and their therapists determine the end of treatment. Because non-randomly missing data can also occur in randomized controlled trials or in observational studies of development, the utility of the SPMM extends beyond naturalistic psychotherapy data." @default.
• W2313005306 created "2016-06-24" @default.
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• W2313005306 date "2014-01-01" @default.
• W2313005306 modified "2023-10-18" @default.
• W2313005306 title "Using a shared parameter mixture model to estimate change during treatment when termination is related to recovery speed." @default.
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• W2313005306 doi "https://doi.org/10.1037/a0034831" @default.
• W2313005306 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4032810" @default.
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