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Folks, I'm trying to print a {texreg} table of lmer() {nlme} and lme() {lme4} models including variances. The variances however, differ significantly between the two model (several orders of magnitude). It seems that the lme() variances are the square root of the lmer() ones. Which ones are correct?

library(plm)
library(lme4)
library(nlme)
library(texreg)
data("Grunfeld", package="plm")
reML0   <-lmer(inv ~ value + capital + (1|firm), data=Grunfeld)
reML1   <- lme(inv ~ value + capital, data=Grunfeld, random=~1|firm)
screenreg(list(reML0, reML1), digits=3, include.variance=TRUE)

========================================================
                            Model 1        Model 2      
--------------------------------------------------------
(Intercept)                   -57.864 *      -57.864    
                              (29.378)       (29.378)   
value                           0.110 ***      0.110 ***
                               (0.011)        (0.011)   
capital                         0.308 ***      0.308 ***
                               (0.017)        (0.017)   
--------------------------------------------------------
AIC                          2205.851       2205.851    
Num. obs.                     200            200        
Num. groups: firm              10                       
Variance: firm.(Intercept)   7366.992                   
Variance: Residual           2781.426                   
Num. groups                                   10        
sigma                                         52.739    
sigma. RE                                     85.831    
========================================================
*** p < 0.001, ** p < 0.01, * p < 0.05
Chris
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1 Answers1

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It seems pretty clear that it's reporting variance for model 1 and sigma for model 2. Variance is sigma squared, so the answer to your question is "both"

heathobrien
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