SAC tests in mixed models

Dear list,

As you may know, the inferences of Moran's I test on model's residuals
change when the model matrix or (X'X)^{-1} are taken into account. It
occurs because regression assumptions affect how we view the regression
residuals.

For example, Moran's I test value of spdep::lm.morantest (which uses the
model matrix) and spdep::moran.test are the same, however, their p-values
are different because the former takes into account the model matrix and
the latter doesn't.

As far as I know ncf::correlog and DHARMa::testSpatialAutocorrelation also
does not account for the model matrix. But I may be wrong about DHARMa.

In general, I think the results of moran.test, correlog and
testSpatialAutocorrelation are reliable for mixed models.

However, I have not found a test like spdep::lm.morantest for mixed models.

Do you also think the results of moran.test, correlog,
testSpatialAutocorrelation are reliable for mixed models? Does anyone know
a SAC test for mixed models which accounts for the models matrix, such as
lm.morantest?

Thanks in advance for any guidance on this topic.

Best,

Vinicius


 <https://rdrr.io/cran/DHARMa/man/testSpatialAutocorrelation.html>