@article{e09debb12dfe4011ae4d95aee813636d,

title = "A reexamination of connectivity trends via exponential random graph modeling in two IDU risk networks",

abstract = "Patterns of risk in injecting drug user (IDU) networks have been a key focus of network approaches to HIV transmission histories. New network modeling techniques allow for a reexamination of these patterns with greater statistical accuracy and the comparative weighting of model elements. This paper describes the results of a reexamination of network data from the SFHR and P90 data sets using Exponential Random Graph Modeling. The results show that {"}transitive closure{"} is an important feature of IDU network topologies, and provides relative importance measures for race/ethnicity, age, gender, and number of risk partners in predicting risk relationships.",

author = "Kirk Dombrowski and Bilal Khan and Katherine Mclean and Ric Curtis and Travis Wendel and Evan Misshula and Samuel Friedman",

note = "Funding Information: 1Because the number of possible configurations of a network progress at a combinatorial (rather than a linear or geometric) rate, our ability to estimate the likelihood of a particular (discovered) configuration against possible random permutations of the same data is much more difficult. This is because, in a network of n individuals, the number of possible configurations of connections (say, for example, risk connections) is 2(n)(n−1)/2. This means that for even a small network of 6 individuals, the number of possible network configurations is 2(6)(5)/2 = 32,768 possible combinations. A network the size of that described in the Social Factors for HIV Risk study (SFHR, discussed below), which contains 767 respondents, would demonstrate 2(767)(766)/2 = 2293,761 possible combinations, an incalculable number in practical terms. This project was supported by National Institute of Health/National Institute on Drug Abuse (NIH/NIDA) Challenge Grant 1RC1DA028476-01/02 awarded to the CUNY Research Foundation and John Jay College, CUNY. The opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect those of the NIH/NIDA. The analyses discussed in this article were carried out at the labs of the New York City Social Networks Research Group (www.snrg-nyc.org). Initial funding for a pilot version of this project was provided by the National Science Foundation Office of Behavioral, Social, and Economic Sciences, Anthropology Program Grant BCS-0752680. Additional support for the project was supplied by the Center for Drug Use and HIV Research (NIDA P30 DA011041). Address correspondence to Prof. Kirk Dombrowski, Department of Sociology, 711 Oldfather Hall, University of Nebraska-Lincoln, Lincoln, NE 68588-0324, USA; E-mail: kirkdombrowski@gmail.com",

year = "2013",

month = dec,

doi = "10.3109/10826084.2013.796987",

language = "English (US)",

volume = "48",

pages = "1485--1497",

journal = "Substance Use and Misuse",

issn = "1082-6084",

publisher = "Informa Healthcare",

number = "14",

}