[R-sig-ME] Observer-level random effects & the variance it they account for...

[Ross Culloch]

Hello all,

I am comparing two GLMMs (please see below), one that includes the observer-level random effect (OLRE) and one that does not. As I understand it, without the OLRE the variance is absorbed in the FINAL_ID_FAC (variance = ca. 0.14). By comparing the two models there is clearly a considerable difference in the variance of the FINAL_ID_FAC, and more importantly  the OLRE, which now explains considerably more of the variance (ca. 0.4) as compared to the FINAL_ID_FAC (ca. 0.12). 

Ultimately, I am interested in using the random effect (FINAL_ID_FAC) to make inference on the importance of considering individual in the model. My concern is that the OLRE is accounting for the variation within and between individuals, which is what I am trying to (somehow) quantify. 

Previous researchers have published without using OLRE (as this field of ecology is constantly evolving this very understandable!). However, my results lead me to different conclusions (by using the BLUPs for each ID in a subsequent analysis) depending on whether or not I include or exclude the OLRE. 

I have posted about this before (many thanks to David Duffy for his reply) and I have read numerous posts from other members that constantly post on this forum, perhaps I have missed the point, but I am still not entirely comfortable with exactly what variation the OLRE is accounting for. 

Many thanks for your time, and any advice you are willing to share!

Ross


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Generalized linear mixed model fit by the Laplace approximation 
Formula: cbind(PC_C_T, PC_C_F) ~ S_ACT_PUP_PROP + S_POOL_DIST + (1 | FINAL_ID_FAC) 
   Data: MODEL_DATA_ID_2009 
  AIC  BIC logLik deviance
 1149 1170 -570.4     1141
Random effects:
 Groups       Name        Variance Std.Dev.
 FINAL_ID_FAC (Intercept) 0.14343  0.37872 
Number of obs: 1525, groups: FINAL_ID_FAC, 15

Fixed effects:
               Estimate Std. Error z value Pr(>|z|)    
(Intercept)    -3.95641    0.11727  -33.74  < 2e-16 ***
S_ACT_PUP_PROP  0.42450    0.05467    7.76 8.21e-15 ***
S_POOL_DIST     0.15400    0.07245    2.13   0.0336 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Correlation of Fixed Effects:
            (Intr) S_ACT_
S_ACT_PUP_P -0.170       
S_POOL_DIST -0.079 -0.045


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Generalized linear mixed model fit by the Laplace approximation 
Formula: cbind(PC_C_T, PC_C_F) ~ S_ACT_PUP_PROP + S_POOL_DIST + (1 | FINAL_ID_FAC) +      (1 | OBS_INDEX) 
   Data: MODEL_DATA_ID_2009 
  AIC  BIC logLik deviance
 1144 1171 -567.2     1134
Random effects:
 Groups       Name        Variance Std.Dev.
 OBS_INDEX    (Intercept) 0.40142  0.63358 
 FINAL_ID_FAC (Intercept) 0.11623  0.34092 
Number of obs: 1525, groups: OBS_INDEX, 1525; FINAL_ID_FAC, 15

Fixed effects:
               Estimate Std. Error z value Pr(>|z|)    
(Intercept)    -4.13969    0.11132  -37.19  < 2e-16 ***
S_ACT_PUP_PROP  0.43440    0.05960    7.29 3.12e-13 ***
S_POOL_DIST     0.15137    0.07498    2.02   0.0435 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Correlation of Fixed Effects:
            (Intr) S_ACT_
S_ACT_PUP_P -0.179       
S_POOL_DIST -0.081 -0.038

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