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Exponential random graph models (ERGMs) are increasingly applied to
observed network data and are central to understanding social
structure and network processes. The chapters in this edited volume
provide a self-contained, exhaustive account of the theoretical and
methodological underpinnings of ERGMs, including models for
univariate, multivariate, bipartite, longitudinal and
social-influence type ERGMs. Each method is applied in individual
case studies illustrating how social science theories may be
examined empirically using ERGMs. The authors supply the reader
with sufficient detail to specify ERGMs, fit them to data with any
of the available software packages and interpret the results.
Exponential random graph models (ERGMs) are increasingly applied to
observed network data and are central to understanding social
structure and network processes. The chapters in this edited volume
provide a self-contained, exhaustive account of the theoretical and
methodological underpinnings of ERGMs, including models for
univariate, multivariate, bipartite, longitudinal and
social-influence type ERGMs. Each method is applied in individual
case studies illustrating how social science theories may be
examined empirically using ERGMs. The authors supply the reader
with sufficient detail to specify ERGMs, fit them to data with any
of the available software packages and interpret the results.
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