[R] interpretation output glmmPQL

From: Emmanuelle TASTARD <tastard_at_cict.fr>
Date: Mon 10 Oct 2005 - 17:09:03 EST


Hi !  

We study the effect of several variables on fruit set for 44 individuals
(plants). For each individual, we have the number of fruits, the number
of flowers and a value for each variable.  

Here is our first model in R :  

y <- cbind(indnbfruits,indnbflowers);
model1
<-glm(y~red*yellow+I(red^2)+I(yellow^2)+densite8+I(densite8^2)+freq8_4+I

(freq8_4^2), quasibinomial);
 

model2 <-
glmmPQL(y~red*yellow+I(red^2)+I(yellow^2)+densite8+I(densite8^2)+freq8_4 +I(freq8_4^2), random=~1|num, quasibinomial);  

      Does it mean that there is no individual effect or is my model not good (number of groups (individuals)=number of observations, is it possible?).  

Thank you by advance for your help  

Emmanuelle TASTARD    

Output model1 :  

Call:
glm(formula = y ~ red * yellow + I(red^2) + I(yellow^2) + densite8 +

    I(densite8^2) + freq8_4 + I(freq8_4^2), family = quasibinomial)  

Deviance Residuals:

    Min 1Q Median 3Q Max -3.4978 -1.5396 -0.1700 0.5210 4.5302  

Coefficients:

              Estimate Std. Error t value Pr(>|t|)    

(Intercept) 2.8076 2.4489 1.146 0.262042
red -1.9290 0.8498 -2.270 0.031738 * yellow -0.3415 1.5189 -0.225 0.823848 I(red^2) 0.3250 0.1229 2.644 0.013700 * I(yellow^2) -0.1776 0.4129 -0.430 0.670573 densite8 -8.2691 4.6140 -1.792 0.084750 . I(densite8^2) 6.0005 3.4666 1.731 0.095318 . freq8_4 9.0044 2.5358 3.551 0.001490 ** I(freq8_4^2) -14.3066 3.8049 -3.760 0.000871 *** red:yellow 0.2320 0.1893 1.226 0.231315
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
 

(Dispersion parameter for quasibinomial family taken to be 5.374839)
Null deviance: 404.64 on 35 degrees of freedom Residual deviance: 137.20 on 26 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 4 Output model2 : Linear mixed-effects model fit by maximum likelihood Data: NULL AIC BIC logLik 112.5895 131.5917 -44.29476 Random effects: Formula: ~1 | num (Intercept) Residual StdDev: 0.02253235 1.968849 Variance function: Structure: fixed weights Formula: ~invwt Fixed effects: y ~ red * yellow + I(red^2) + I(yellow^2) + densite8 + I(densite8^2) + freq8_4 + I(freq8_4^2) Value Std.Error DF t-value p-value
(Intercept) 2.805933 2.449548 26 1.145490 0.2624
red -1.927214 0.850055 26 -2.267164 0.0319 yellow -0.343353 1.519357 26 -0.225986 0.8230 I(red^2) 0.324676 0.122961 26 2.640481 0.0138 I(yellow^2) -0.177084 0.412955 26 -0.428820 0.6716 densite8 -8.265473 4.615384 26 -1.790853 0.0850 I(densite8^2) 5.997720 3.467743 26 1.729574 0.0956 freq8_4 9.006669 2.535929 26 3.551625 0.0015 I(freq8_4^2) -14.309852 3.804955 26 -3.760847 0.0009 red:yellow 0.231987 0.189296 26 1.225523 0.2314 Correlation: (Intr) red yellow I(r^2) I(y^2) denst8 I(8^2) frq8_4 I(8_4^ red -0.562 yellow -0.581 -0.179 I(red^2) 0.467 -0.934 0.248 I(yellow^2) 0.240 0.481 -0.896 -0.451 densite8 -0.764 0.369 0.196 -0.338 0.075 I(densite8^2) 0.743 -0.326 -0.208 0.327 -0.038 -0.987 freq8_4 -0.100 -0.112 0.171 -0.041 -0.254 -0.016 -0.086 I(freq8_4^2) 0.141 0.001 -0.061 0.140 0.095 -0.150 0.240 -0.938 red:yellow 0.585 -0.634 -0.113 0.355 -0.308 -0.468 0.383 0.375 -0.237 Standardized Within-Group Residuals: Min Q1 Med Q3 Max -1.66511749 -0.59215881 -0.08635717 0.26740423 2.75720770 Number of Observations: 36 Number of Groups: 36 Emmanuelle TASTARD UMR 5174 'Evolution et Diversité Biologique' Université Paul Sabatier Bat 4R3 31062 TOULOUSE CEDEX 9 France tel : 05 61 55 67 59 [[alternative HTML version deleted]]

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Received on Mon Oct 10 17:14:00 2005

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