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Hello,

the LME model accounts for dependencies between timepoints, but does so in a flexible way: it does not require the same number of observations for each participant, nor does it require identical intervals between observations. Also including a single timepoints for some cases is fine.

In general, one can think of it as a regression problem: sometimes more data/timepoints are available to model the slopes across time, sometimes less. This probably affects the precision of the estimates, but apart from that, varying numbers of timepoints and variable intervals are not a fundamental problem for LME models.

Best regards,

Kersten

Am 10.07.2023 um 22:11 schrieb Lara Foland-Ross <lfoland@stanford.edu>:

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Hi there, 

We have a longitudinal structural neuroimaging dataset with anywhere between 1 and 4 timepoints collected for each participant. How does LME handle missing data when analyzing longitudinal trends? 

Thanks,
Lara

Lara Foland-Ross, Ph.D.
Senior Research Associate and Imaging Lab Manager
Center for Interdisciplinary Brain Sciences Research
Stanford University School of Medicine
401 Quarry Road, Room 1356
Stanford, CA 94305-5795
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Kersten Diers
Image Analysis Group (AG Reuter)
German Center for Neurodegenerative Diseases (DZNE) 
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