Greetings:
With Jeff's help I have managed to figure out how to bin up an age*time model for a 3 age group model (2 sex groups too, but not relevant). I can compare estimates to regurlar MARK and all seems fine. To figure out how to output model averaged values, I started easy by creating 2 models Phi(age*t) p(.) and Phi(t) p(.) as shown in the code below. The issue is when I try to model average the 2 models I get the error message:
Warning messages:
1: In get.real(model, parameter.names[i], se = se, show.fixed = show.fixed) :
Improper V-C matrix for beta estimates. Some variances non-positive.
2: In get.real(model, parameter.names[i], se = se, show.fixed = show.fixed) :
Improper V-C matrix for beta estimates. Some variances non-positive.
When I look at the VC for the betas in regular P MARK there are no non-positive varinaces. In fact, all looks hunky-dory with no weird estimates or SEs. What am I missing.
And thanks for your help already (esp you Jeff). Cheers, Mary
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SIE_cjs.ddl=add.design.data(SIE_cjs.process,SIE_cjs.ddl,"Phi",type="age",
bins=c(0,1,2,27),
right=FALSE,name="ageclass",replace = T)
Phi.age.time=list(formula=~ageclass*time)
Phi.time=list(formula=~time)
p.dot = list(formula=~1)
Phi.age.t_p.dot=mark(SIE_cjs.process,SIE_cjs.ddl,model.parameters = list(Phi=list(formula=~ageclass*time),p=p.dot))
Phi.time_p.dot=mark(SIE_cjs.process,SIE_cjs.ddl,model.parameters = list(Phi=Phi.time,p=p.dot))
SIE_cjs_results=collect.models()
mod_avg=model.average(SIE_cjs_results)