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I am running a mixed-effects model in R and I want to have random intercepts for two sampling levels, country and site. The variable site is perfectly nested within the level country. So, is it necessary to model a separate term for the random intercept of country, or will simply modeling the error for site be suitable?

I.e., would the model

lmer(outcome ~ predictor + (1|country) + (1|site))

have any benefit over the model

lmer(outcome ~ predictor + (1|site))
Amadou Kone
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  • I think you meant to use random intercepts in your title? Do you have multiple sites for each country? – Isabella Ghement May 15 '18 at 21:57
  • Thanks @IsabellaGhement. I did mean random intercepts. And I do have random sites for each country. I should add that I am mostly interested in getting good estimates for my (fixed) predictor variable. – Amadou Kone May 16 '18 at 19:09
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    There may be a country characteristic that effects your predictor. I would add the country level, though I'm relatively new to MLM. – dankernler May 16 '18 at 20:07
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    If `site` is nested within `country`, then the correct specification of the random effects would be: `(1|country/site)`. For more information, see [here](https://stats.stackexchange.com/a/228814/21054). Your current specification is for crossed random effects. – COOLSerdash May 17 '18 at 07:14

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