MELD specifications


Unique identifier OMICS_34210
Alternative name Mixed Effects for Large Datasets
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
License GNU General Public License version 3.0
Computer skills Advanced
Stability Stable
Maintained Yes




No version available


  • person_outline Per Sederberg

Publication for Mixed Effects for Large Datasets

MELD citation


MELD: Mixed effects for large datasets

PLoS One
PMCID: 5567894
PMID: 28829807
DOI: 10.1371/journal.pone.0182797

[…] lly prohibitive for large datasets. The computational cost is further exacerbated if one still wants to take advantage of nonparametric resampling and TFCE. We have developed a novel technique called Mixed Effects for Large Datasets (MELD) that makes it easy to apply permutation testing, TFCE, and LMER to the type of large datasets commonly found in neuroimaging research. Here we explain in detail […]

MELD institution(s)
Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD,USA; Department of Psychology, The Ohio State University, Columbus, OH, USA
MELD funding source(s)
Supported by the Choose Ohio First for Bioinformatics Scholarship.

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