Dear all,
I am new to mixed model and I have a question regarding GAMM. Hope you can give me some insightsI would like to model the response variable (e.g. biomass) in relation with year, sampling depth, sampling water visibility. In the model, residual variance is set as different per year. Additionally, because sampling was done at repeated sites during the year (sometimes at repeated site in the same year), I choose site as random intercept. The water visibility shows a non-linear relationship with response variable, therefore, I choose gam to model it with a smoother.
f1_gam <- formula(response~year + depth + s(visibility)) vf1 <- varIdent(form= ~1 | year)M1_gam <- gamm(f1_gam, random = list(site= ~1), weights = vf1,             method="REML", na.action=na.omit, data=Dat) 
1) besides the biological as aspect, is this model technically sound? I would like to model year as a fixed effect (because I am interested in it), but seems that year and site have crossed-random effect.
2) what does the scale.est in summary(M1_gam$gam) mean? does it still mean the variance of the residuals?
3) From summary(M1_gam$lme)l, only printed the ratios of yearly variance. I couldnt find the absolute value?
Could someone help me with this?
Thanks
  		 	   		  
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