[statnet_help] Question about including an interaction effect in REM

[SJ C via statnet_help]

Dear all,

May I ask a question about including an interaction effect in REM?
As illustrated in the code below, let's say I have two variables, A.cat
(categorical) and B.con (continuous).

  rem.dyad(networkdata, n = 200, effects = c("CovSnd","CovRec", "CovEvent",
                                                 "NIDRec","NIDSnd",
                                                 "NODSnd","NODRec",
                                                 "PSAB-BA",
                                                 "RRecSnd", "RSndSnd"),
              covar = list(CovSnd = cbind(A.cat, B.con),
                              CovRec= cbind(A.cat, B.con),
                              CovEvent = abind(same.A.cat, A.cat*B.con,
along=0)),
                              ordinal=TRUE, hessian = TRUE)

To create their interaction effect, I formed a matrix by inserting senders'
A.cat values into all columns except the diagonal.
Additionally, I did the same thing with senders' B.con values and
mean-centered them.
Then, I multiplied these two matrices, which is represented as A.cat*B.con
in the code.

My questions are:
1. Can the interaction term be inserted into the REM in the way described
above?
2. Should I also include A.cat and B.con(centered) as components in the
CovEvent code, along with A.cat*B.con?

Besides these questions, I am also curious whether there are any measures
or indices that can compare the statistical significance of coefficients
between two REMs with the same parameters?

It would be greatly appreciated if I can have any responses.
Thank you!

Sincerely,
Choi
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