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mixed effect model: compare seed families

Hi,

Thanks to Mike and Thierry for suggestions. The key points were that the 
random factors are crossed, and it can be analysed by lmer.

I've done the analysis, and the results considerably differ from which 
I've get without including random factors.

It was strange for me that lmer calculate t-statistic for each parameter 
estimates, but it does not show neither df nor p-value.

For example (from the help of lmer):

 > (fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
Linear mixed model fit by REML
Formula: Reaction ~ Days + (Days | Subject)
   Data: sleepstudy
  AIC  BIC logLik deviance REMLdev
 1756 1775 -871.8     1752    1744
Random effects:
 Groups   Name        Variance Std.Dev. Corr 
 Subject  (Intercept) 612.092  24.7405       
          Days         35.072   5.9221  0.066
 Residual             654.941  25.5918       
Number of obs: 180, groups: Subject, 18

Fixed effects:
            Estimate Std. Error t value
(Intercept)  251.405      6.825   36.84
Days          10.467      1.546    6.77

Correlation of Fixed Effects:
     (Intr)
Days -0.138

I could test factors only by comparing two models using anova function 
that calculates ML-Chisq (I tried the test="F" parameter, but it did not 
influence the result). I hope it is correct.

Thanks again, and best wishes

Zoltan


Dunbar, Michael ?rta: