robustlmm function rlmer() too slow

Asked Aug 04 '20 at 21:50

Active Aug 04 '20 at 22:24

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I want to conduct a mixed model with robust standard errors in a dataset with 45,000 rows. When I try to run the below code using rlmer() from the robustlmm package, it doesn't produce any result within 10 minutes (and probably longer). Y is continuous 1-12, x is binary, and PID is continuous 1:3000.

rlmer(y ~ x + (1|ID), data=dta_long)

Thank you in advance,

Benji

edit: the model runs fine when I use just the first 100 rows of the dataset. Looks like I just need someway to make it speedier.

edited Aug 04 '20 at 22:24

asked Aug 04 '20 at 21:50

Benji

1

How big is the dataset `dta_long`? Did you try with some small sample data first? – Samuel Aug 04 '20 at 22:08
Thanks for your response, I tried it with just the first 100 rows and it produced a result. The full dataset is 45,000 rows. – Benji Aug 04 '20 at 22:22
And how many columns? Three? – Samuel Aug 04 '20 at 23:18
Yep, just three columns. – Benji Aug 05 '20 at 17:50

robustlmm function rlmer() too slow

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