[statnet_help] Examples of dynamic population equilibria with more than two groups in EpiModel stochastic network models

martina morris morrism at uw.edu
Sat Oct 31 12:46:22 PDT 2020

Hi Benji -- you should post this on the EpiModel listserv.


On Sat, 31 Oct 2020, b wrote:

> I am trying to incorporate custom arrival and departure modules into a network model (SEIRQ) with 4 different "types" of

> individuals (still in v1.8). The context interprets "arrivals" and "departures" as replacements for each other from a

> fixed reservoir, without actual deletion of these nodes as in the mortality module. The total N is fixed. When one

> "departs", they can no longer form partnerships, and an arrival of the same type replaces that individual, until a few

> time steps later, when the exchange happens again. How many time steps later is determined by the type, and each of the 4

> types has unique durations to remain in and out of the network (mimicking their work schedule, independent of status). I

> am having difficulty coding this population to maintain a dynamic equilibrium. It would be easier in a .icm with 2 groups

> or types that each arrived for X days, then departed for X days, with all the rates balancing.

> Surprisingly, I haven't been able to find any examples in the literature of EpiModel network models using

> (non-birth/death) arrival and departure modules with a fixed population. If you can point me in the direction of an

> example, it would be very instructive to see how dynamic equilibrium is coded into a network model with more than two

> groups when you can't simply calibrate birth and death rates to equilibrium.


> Thanks,

> Benji Zusman

> University of Florida



> On Mon, Oct 12, 2020, 3:02 PM <statnet_help-request at mailman13.u.washington.edu> wrote:

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> Today's Topics:


>    1. How does ERGMs deal with parameters that cannot be estimated

>       from the data? (David Kretschmer)




> ---------- Forwarded message ----------

> From: David Kretschmer <dkretsch at mail.uni-mannheim.de>

> To: statnet_help at u.washington.edu

> Cc:

> Bcc:

> Date: Mon, 12 Oct 2020 17:23:17 +0200

> Subject: [statnet_help] How does ERGMs deal with parameters that cannot be estimated from the data?

> Hello dear list users,


> I estimate an ERGM that includes a parameter that cannot be estimated from the data, i.e., it contains a dyadic

> covariate that has the value zero for each dyad.


> To my surprise, running an ERGM on this data does still provide a coefficient estimate for the parameter that

> cannot be estimated from the data. Under normal conditions, the coefficient estimate is zero, and the standard

> error and all other elements in the ERGM output are NA. Still, I wondered why a coefficient value of zero is

> reported even though the parameter clearly cannot be estimated from the data.


> Furthermore, when using the “constraints” argument of ERGM (constraints = ~bd(maxout = 5) in my case), the reported

> coefficient estimate is no longer zero but some other, seemingly random value that frequently is very high (e.g. 51

> in one example run). Here, I also wonder how the ERGM arrives at this value.


> In general, it is clear to me that these coefficient estimates are without substantive meaning. However, I wonder

> why they are still reported in the ERGM output and how the corresponding values come about.


> Any help would be greatly appreciated.


> Best,

> David




> --

> David Kretschmer

> Universität Mannheim

> Mannheimer Zentrum für Europäische Sozialforschung (MZES)

> A5, 6

> 68159 Mannheim

> Tel.: +49-621-181-2024


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