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So for random mixed effects, I am making a comparison list of scripts between the 2 packages.

For independent random intercept and slope, if I am using the following code in lme4 package, what is the corresponding script in nlme?

model1 <- lmer(y~A + (1+site) + (0+A|site), data, REML = FALSE)

Also, for nested mixed effects, which calculates the random effect in different way from the above, are my scripts correct?

model2 <- lme(y~A, random = ~1+site/A, data, method="REML")

and

model3 <- lmer(y~A + (1|site) + (1|site:A), data, method=FALSE)

Thank you so much!

AS Mackay
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Hamham Rhapsody
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1 Answers1

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I hope this answer is not too late!

For your first model the version in nlme would be:

model1 <-  lme(y ~ A , 
       random = list(A = pdDiag(~time)),
       data=data)

Your seccond and third models are equivalent. Model 3 in lme4 package can be also written as:

 model3 <- lmer(y~A + (1|site/A), data, method=FALSE)

I foud this link that might help you a lot to compare nlme and lme4 packages

https://rpsychologist.com/r-guide-longitudinal-lme-lmer#conditional-growth-model-dropping-intercept-slope-covariance

ichisa
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