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SOCNET  November 2014

SOCNET November 2014

Subject:

siena vs. relational event

From:

Katerina Bohle Carbonell <[log in to unmask]>

Reply-To:

Katerina Bohle Carbonell <[log in to unmask]>

Date:

Thu, 6 Nov 2014 07:45:22 -0500

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text/plain (48 lines)

***** To join INSNA, visit http://www.insna.org *****

Hello,

I collected data in a simulation center (emergency care teams). The network
(information exchange) is coded from the videos. I have 33 group.
I want to look at how the interaction pattern changes with regard to changes in the
patients health, so the context plays a role. But for every group, the frequency and
sequence, with which the patient's health changes, is different, and the length of
time the patient is in good/regular/bad health is also different.

I'm struggling with two points for the analysis:

1) I have been using siena in the past and I know that if I want to use the
multigroup option I need to have the same amount of waves for every group. I
also believe that every wave needs to last the same amount of time (e.g. 5
minutes). Am I correct?

2) The assumption, of what a tie is, is different in siena and relational event
modeling. The former assumes it to be a state (enduring) whereas the latter an
event (discrete). I believe that in the emergency care teams as network ties are
measured as person A talking to person B, the assumption of a discrete event
applies (similar to the radio communication example mentioned in Butts (2008).
The issue is that this study is part of my PhD and as I'm in the Netherlands, the
dissertation is in the form of a collection of articles. Another study, which is
included in the dissertation, uses siena. So I have two chapters, which follow each
other, with different assumptions for what a tie is. Therefore my arguments need
to be clear and convincing. In short this is what I argue: "When measuring
information sharing by asking respondents to state 'how frequently they share
information with person X over the past 3 months', the tie is operationalized as an
enduring state. In this situation, it is assumed that - if everything else remains
constant - the tie will continue to exists. However, when measuring information
sharing by looking at every instant of interaction, the tie is not anymore enduring,
but discrete." So my basic argument is that I measure the tie differently, and
therefore have to use a different method. Is this convincing? Do I miss something?

Thank you for your help,
Katerina

Researcher
Department of Educational Research and Development
Maastricht University

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