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This requires to develop the fast-and-robust bootstrap methodology for robust estimators of multilevel models. Such robust estimators are implemented in package [`robustlmm`](https://cran.r-project.or…
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I'm interested in using the csSampling package to run multilevel models on complex survey data, but I didn't succeed in fitting a simple random-intercept model. After the Stan model was fit, the proce…
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run:
`USE_LADE=1 LOAD_LADE=1 python minimal.py`
result:
```
Traceback (most recent call last):
File "/home/workspace/LookaheadDecoding/minimal.py", line 32, in
greedy_output = model.gener…
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Hi Jasper,
After using your package, I had an idea to merge it with something I worked on for my specialization thesis. I worked on Marginalized Multilevel Models (not to be confounded with Marginal …
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I am interested in fitting a spatial multilevel model using the tidymodels framework. In the [Spatial Regression](https://r-spatial.org/book/16-SpatialRegression.html) chapter of [_Spatial Data Scienc…
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Currently there is a barebones set up for running multilevel models, this needs to be extended and made more functional.
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The motivation behind this idea is the `depression_unemployment` data. Although it was only used by Singer and Willett in chapter 5 to demonstrate the multilevel model for change, the data contains in…
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Hi,
I can't find the answer to why I get 0 power using powerSim on a multilevel model.
This is my model
```
model.of.interest.1
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At the moment, Case Study 1 is about _linear_ multilevel models. Should we make it about more general multilevel models generally, particularly including multilevel logistic regression.
I have Jags …
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I suggest that the starting point is what Cassandra, Hu, and I used in https://github.com/fsolt/dcpo_dem_mood, but an alternative is go with `brms` as in https://github.com/fsolt/dcpo_macrointerest. …
fsolt updated
2 weeks ago