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meld's Introduction

MELD:

Mixed Effects for Large Datasets

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MELD uses rpy2 to wrap r's LME4 library. rpy2 is sometimes difficult to install, so we've provided a docker image with MELD, rpy2, and a jupyter notebook. Just run docker run --rm -p 8888:8888 compmem/meld to start MELDing.

If you use MELD, please cite our publication: Nielson DM, Sederberg PB (2017) MELD: Mixed effects for large datasets. PLOS ONE 12(8): e0182797. https://doi.org/10.1371/journal.pone.0182797

This repo is very much a work in progress, but MELD works in python 3, and is distributed with a docker container to alleviate the pain of rpy2 installation.

meld's People

Contributors

shotgunosine avatar bilgelm avatar leej3 avatar

Stargazers

 avatar Stefan Repplinger avatar Hyungwook Yim avatar

Watchers

Per B. Sederberg avatar James Cloos avatar  avatar  avatar Ian K. Schleifer avatar  avatar

meld's Issues

Error on running run_perms() in tutorial

I am trying to do mixed-effects modeling of 128-channel ERP data. I found MELD to be a perfect match for my needs.

I ran the provided docker container and the tests (runtests.sh) successfully.
While going through the tutorial file MELD_example.ipynb I encountered runtime errors on executing run_perms(). Here is the full log; also .txt attached here.

It appears to be an issue with something rpy2 is trying to do.

I have 3 questions:

  1. Is this project being actively maintained? The last commit was more than a year ago.
  2. Is there any documentation for MELD? The provided example file was not quite intuitive to me, past the simulation bits.
  3. Short of any other tutorials, is this code for the 2017 paper a more suitable tutorial? It is a bit better commented, but I'm not sure if the current, more updated repo, matches the older one.

Having gone through the 2017 paper, I find this quite exciting and I hope I can use it for modeling my data. Any help in lowering the barrier to that would be appreciated.

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