CODEWITHSUNDEEP
rcovariancelme4
OCT
OCT

Reputation: 71

Covariance parameter estimates table in R

I have created a random intercept and slope model (lmer) and need to inspect the covariances of the random effects to see which is significant.

I've seen that SAS outputs provide a 'covariance parameter estimates' table as part of the model summary - see section 'Output 56.2.6 Repeated Measures Analysis' of PROC MIXED

Is there a way of doing this (and obtaining p values for each covariance) in R?

Upvotes: 5

Views: 1476

Answers (1)

JAD
JAD

Reputation: 2170

Yes, you can find this in the output of the summary of your model:

x <- lm(formula)
y <- summary(x)
print(y$cov.unscaled)

From the documentation of ?summary:

cov.unscaled a p x p matrix of (unscaled) covariances of the coef[j], j=1, …, p.

Upvotes: 2

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