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METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20220301T113112Z
DTSTART:20220302T160000Z
DTEND:20220302T170000Z
SUMMARY:Mitchell Centre seminar series
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}i12d-kyvnan
0j-efwbzq
DESCRIPTION:Michal Bojanowski\nKozminski University\n\nExponential-family
Random Graph Models for egocentrically-sampled data: examples and new d
evelopments with illustrations using data on core discussion networks\n\
nEgocentric sampling of networks selects a subset of nodes ("egos") and
collects information from them on themselves and their immediate network
neighbours ("alters")\, leaving the rest of the nodes in the network un
observed. This design is popular because it is relatively inexpensive to
implement and can be integrated into standard sample surveys. Recent wo
rk has shown that data collected through an egocentric design can be use
d to estimate certain specifications of Exponential-family Random Graph
Models (ERGM). In particular\, data about the egosâ€™ immediate connection
s can be used to estimate models with nodal\, degree\, and mixing effect
s. This talk will first review the proposed modeling approach focusing o
n (1) survey sampling design and measurement considerations\, (2) types
of model terms that are identifiable\, and (3) properties of the model i
n its ability to recover whole-network features. It will then proceed to
present results of a new re-analysis of GSS 2004 data with a question a
bout the effect of marriage ties on the structure of core discussion net
works - an analysis showcasing how to estimate models with effects of dy
adic covariates which are *not* functions of observed node attributes. T
he talk will conclude with a discussion of advantages and limitations of
the presented approach.\n
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:G6\, Humanities Bridgeford Street\, Manchester
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