Skip to content

Questions on Mixed Model analysis

2 messages · Cleber Iack, Ben Bolker

#
Dear,

I would like if it was possible that the Lord would help me in a review,
lest it incur in error.

If it were a Simple Logistic regression, I  in school "A" could calculate
the Odds Ratio for example in relation to the "P1", I would exp
(-0.44448621), but since I'm using a generalized linar mixed model with
Reply Binaria, I can analyze the same way this exit?

If I'm wrong, could you give me an example of these data down the analysis
of any school cited in relation to any predictor variable

Thank you

Cleber
$escola
      (Intercept)          P1                P2              P3
 P4
A     1.6902746  -0.4448621  -0.6658758 -3.4604301  -3.3696828
B   -1.2843136   1.0089079   0.3088816  0.1211393   1.6589110
C  -0.5780668  -0.9977792   0.5655049  2.1674668   0.1728413
D   0.1886338   0.4412192  -0.2184985  1.5010123   1.7992507"

Number of obs: 79811, groups:  escola, 4
Fixed Effects:
    (Intercept)              cem       anoscMedio       anoscMuito
 anoscFinalizado
       -2.44242         -0.22111         -0.53089         -1.80689
-2.45414
           cugm              cri              cam              hpm
    caim
        0.06979         -0.55041          0.20136          0.17523
-0.12234
            cpm             qutm              ism                     P1
               P2
        0.21953         -0.06551          0.07528         -0.64913
-1.50175
     P3                        P4
       -2.19105         -1.88287
#
On Tue, Nov 22, 2016 at 1:38 PM, Cleber Iack <profiack at gmail.com> wrote:
The random effects represent deviations from the population-level
value of the parameter.  So the odds ratio represents the deviation
from the population average.  If you want the overall odds ratio
(deviation of school A from even odds in the P1 parameter), try coef()