offset.linear.predictor

[shicx]

Hello!

After fitted a poisson model, what is the difference between offset.linear.predictor and summary.linear.predictor in result.

Thanks.

[Helpdesk (Haavard Rue)]

> r=inla(y ~ 1, data=data.frame(y=1))
> r$summary.linear.predictor[1,"mean"]
[1] 0.9999969735
> r$offset.linear.predictor[1]
[1] 0
> r=inla(y ~ 1, data=data.frame(y=1), offset=2)
> r$summary.linear.predictor[1,"mean"]
[1] 0.9999969735
> r$offset.linear.predictor[1]
[1] 2
> r=inla(y ~ 1 + offset(-2), data=data.frame(y=1), offset=2)
> r$summary.linear.predictor[1,"mean"]
[1] 0.9999969735
> r$offset.linear.predictor[1]
[1] 0

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[shicx]

Thank you for your reply, for the following example, I would like to ask if it is possible to go to calculate the intercept.linear.predictor. e.g. r$summary.linear.predictor[1, "mean"]-r$offset.linear.predictor[1]?

> r=inla(y ~ 1, data=data.frame(y=1), offset=2)
> r$summary.linear.predictor[1, "mean"]
[1] 0.9999969735
> r$offset.linear.predictor[1]
[1] 2

[Helpdesk (Haavard Rue)]

I do not understand what you mean. the offset goes into the linear
predictor and the offset.linear.predictor is there to keep track of the
offset variable, as it can come in from several sources.

you can also get the intercept itself, using r$summary.fixed

[shicx]

If there are covariates x in the equation, I want to get eta with only intercept and covariates, i.e., liear.predictor with offset removed. because i guess this can be used in a with-offset poisson model to predict the incidence of points with no offset value.

> r=inla(y ~ 1+x, data=data.frame(y=1,x=2), offset=2) > r$summary.linear.predictor[1, "mean"] [1] 0.9999999 > r$offset.linear.predictor[1] [1] 2

[Helpdesk (Haavard Rue)]

you just subtract the offset then, right?

[shicx]

yes.

Thank you！