[datatable-help] Fitting interaction term in GAMM with random effect
SamLC
slcox417 at gmail.com
Tue Apr 5 16:54:10 CEST 2016
Hi,
I am trying to fit a model with a random effect of DeploymentID with a
nested AR1 autoregressive correlation structure. For the fixed component I
am fitting a smooth of tide. I have two sets of models I am fitting with
different data sets. For the smooth of tide, I want a separate smooth to be
fitted per SiteID. In one set of models this is fine (each SiteID contains
multiple DeploymentIDs). In the other SiteID and DeploymentID are
identical. I am wondering how to code this. I am not interested in the
intercept of SiteID hence why it has previously been a random effect. I am
interested in how smooths vary between SiteIDs and hence why this is a fixed
effect.
Example data structure first data set:
SiteID DeploymentID
1 1
1 1
1 1
1 1
1 1
1 2
1 2
1 2
1 3
2 4
2 4
2 4
2 4
2 4
2 5
2 5
2 5
3 6
3 7
3 8
etc etc
Example data structure seconddata set:
SiteID DeploymentID
1 1
2 2
3 3
4 4
My problem is that I understand to fit a interaction term, one must use
gamm(Y~s(tide,k=5,bs="cc",by=SiteID)+SiteID,knots=list(tide=c(0,1)),correlation=corAR1(form=~1|DeploymentID).....
- if I include +SiteID then I should NOT include DeploymentID as a random
effect also (for the second model where SiteId and DeploymentID are
identical - but this is ok for the first model)?
-the problem is when I want to compare nested models I run into issues if
the smooth term is dropped as I do not have a random or smooth term in the
model.
Can I code as
gamm(Y~s(tide,k=5,bs="cc",by=SiteID),knots=list(tide=c(0,1)),random=list(DeploymentID=~1),correlation=corAR1(form=~1|DeploymentID).....
Any help on this is appreciated....
Cheers
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