absdiffby summary statistic

[DamienGeorges]

Hi Sam, Hi all,

I want to use absdiffby than I need to compute the target.

I can't find any fully explicit help file of absdiffby term. (here is the actual help file right? https://github.com/statnet/EpiModelHIV/blob/master/R/ErgmTerms.R )

Could you please tell me what this summary stat is exactly?

Which is the ref category? (e.g. by arg is sex and coded 0/1)
What the arg assym stands for?
Is the term code is https://github.com/statnet/EpiModelHIV/blob/master/src/changestats.users.c ?

Thanks,
Damien

[martinamorris]

Hi Damien,

Sam is offline for a bit, so I'll try to pinch hit here.

The code for user written ergm terms (like this one) has two pieces, one is the R code you note above, the other is the C code that actually does the calculation, here:

https://github.com/statnet/EpiModelHIV/blob/master/src/changestats.users.c

I'm not a C coder, but this is a pretty simple term. Its primary purpose is to modify the vanilla absdiff term to allow for an "asymmetry" in the age differences by a binary variable like sex: males are typically older than their female partners, and you can take the average difference in age as an "offset" to recenter the age difference to 0 at that value. Net of this offset, the difference in ages then works as before.

As the code shows, when the by variable=1, the contribution to the term is

INPUT_PARAM[t] - INPUT_PARAM[h] - offset

and when =0

INPUT_PARAM[t] - INPUT_PARAM[h] + offset

So, when by=sex, and E(age(M)-age(F)) > 0, M should be coded 1, and F should be coded 0.

LMK if this makes sense.

@sgoodreau pls add comments or corrections as needed :)

[sgoodreau]

That matches my understanding perfectly.  As an example, if you have absdiffby(age, by=sex, offset = 2) and M is coded as 1 and F as 0, then A relationship between a 30-yo M and 25-yo F will contribute 3 to the statistic A relationship between a 30-yo M and 26-yo F will contribute 2 to the statistic A relationship between a 30-yo M and 27-yo F will contribute 1 to the statistic A relationship between a 30-yo M and 28-yo F will contribute 0 to the statistic A relationship between a 30-yo M and 29-yo F will contribute 1 to the statistic A relationship between a 30-yo M and 30-yo F will contribute 2 to the statistic A relationship between a 30-yo M and 31-yo F will contribute 3 to the statistic Make sense? Steve

…

On 10/15/2018 4:02 PM, Martina Morris wrote: Hi Damien, Sam is offline for a bit, so I'll try to pinch hit here. The code for user written ergm terms (like this one) has two pieces, one is the R code you note above, the other is the C code that actually does the calculation, here: https://github.com/statnet/EpiModelHIV/blob/master/src/changestats.users.c I'm not a C coder, but this is a pretty simple term. It's primary purpose is to modify the vanilla absdiff term to allow for an "asymmetry" in the age differences by a binary variable like sex: males are typically older than their female partners, and you can take the average difference in age as an "offset" to recenter the age difference to 0 at that value. Net of this offset, the difference in ages then works as before. As the code shows, when the by variable=1, the contribution to the term is INPUT_PARAM[t] - INPUT_PARAM[h] - offset and when =0 INPUT_PARAM[t] - INPUT_PARAM[h] + offset So, when by=sex, and E(age(M)-age(F)) > 0, M should be coded 1, and F should be coded 0. LMK if this makes sense. @sgoodreau <https://github.com/sgoodreau> pls add comments or corrections as needed :) — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#51 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AH3lgi0ypXfEi6NrS3D9gDFNWQQapIHbks5ulRQYgaJpZM4XZcnZ>.

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[DamienGeorges]

Excellent!
Thanks a lot!
That makes lot of sense and adding this term to my network make the model outputs much more realistic!
Thanks one more time for the kind and fast assistance.
Damien