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Airoldi EM, Blei DM, Fienberg SE, et al.
Mixed Membership Stochastic Blockmodels
J MACH LEARN RES 9: 1981-2014 SEP 2008
Zanghi H, Ambroise C, Miele V
Fast online graph clustering via Erdos-Renyi mixture
PATTERN RECOGN 41 (12): 3592-3599 DEC 2008
Hsieh MH, Magee CL
An algorithm and metric for network decomposition from similarity matrices:
Application to positional analysis
SOC NETWORKS 30 (2): 146-158 MAY 2008
Handcock MS, Raftery AE, Tantrum JM
Model-based clustering for social networks
J ROY STAT SOC A STA 170: 301-322 Part 2 2007
Buntine W, Jakulin A
Discrete component analysis
LECT NOTES COMPUT SC 3940: 1-33 2006
Brandes U, Erlebach T
Network analysis - Methodological foundations - Introduction
LECT NOTES COMPUT SC 3418: 1-+ 2005
Tallberg C
A Bayesian approach to modeling stochastic blockstructures with covariates
J MATH SOCIOL 29 (1): 1-23 JAN-MAR 2005
Nowicki K, Snijders TAB
Estimation and prediction for stochastic blockstructures
J AM STAT ASSOC 96 (455): 1077-1087 SEP 2001
p(2): a random effects model with covariates for directed graphs
van Duijn MAJ, Snijders TAB, Zijlstra BJH
STATISTICA NEERLANDICA
58 (2): 234-254 MAY 2004
Abstract:
A random effects model is proposed for the analysis of binary dyadic data that represent a
social network or directed graph, using nodal and/or dyadic attributes as covariates. The
network structure is reflected by modeling the dependence between the relations to and from
the same actor or node. Parameter estimates are proposed that are based on an iterated
generalized least-squares procedure. An application is presented to a data set on friendship
relations between American lawyers.
Author Keywords:
adjacency matrix, dependent binary data, GLMM, IGLS, logistic regression, p(1) model,
random effects, social network analysis
KeyWords Plus:
GENERALIZED LINEAR-MODELS, LOGISTIC-REGRESSION MODELS, SOCIALRELATIONS MODEL, MULTILEVEL MODELS, LOGIT-MODELS, STATISTICALANALYSIS, MAXIMUM-LIKELIHOOD, BINARY RESPONSE, STOCHASTIC
BLOCKMODELS, RELATIONAL DATA
Addresses:
van Duijn MAJ, Univ Groningen, ICS Heijmans Inst, Dept Sociol Stat & Measurement
Theory, Grote Rozenstr 31, NL-9712 TG Groningen, Netherlands
Univ Groningen, ICS Heijmans Inst, Dept Sociol Stat & Measurement Theory, NL-9712 TG
Groningen, Netherlands
Publisher:
BLACKWELL PUBL LTD, OXFORD
IDS Number:
801HQ
ISSN:
0039-0402
Handcock MS, Raftery AE, Tantrum JM
Model-based clustering for social networks
J ROY STAT SOC A STA 170: 301-322 Part 2 2007
Snijders TAB, Robinson T, Atkinson AC, et al.
Discussion on the paper by Handcock, Raftery and Tantrum
J ROY STAT SOC A STA 170: 322-354 Part 2 2007
Wong LH, Pattison P, Robins G
A spatial model for social networks
PHYSICA A 360 (1): 99-120 JAN 15 2006
Zijlstra BJH, van Duijn MAJ, Snijders TAB
Model selection in random effects models for directed graphs using approximated
Bayes factors
STAT NEERL 59 (1): 107-118 FEB 2005
Asymptotic null distribution of person fit statistics with estimated person parameter
Snijders TAB
PSYCHOMETRIKA
66 (3): 331-342 SEP 2001
Abstract:
Person fit statistics are considered for dichotomous item response models. The asymptotic
null distribution is derived for statistics which are linear in the item responses, and in which
the ability parameter is replaced by an estimate. This allows the asymptotically correct
standardization of linear person fit statistics with estimated ability parameter. The fact that the
ability parameter is estimated usually decreases the asymptotic variance.
Author Keywords:
item response theory, person fit, asymptotic approximations
KeyWords Plus:
APPROPRIATENESS MEASUREMENT, LATENT TRAIT, INDEXES, MODEL
Addresses:
Snijders TAB, Univ Groningen, Dept Stat Measurement Theory & Informat Technol, NL9712 TS Groningen, Netherlands
Univ Groningen, Dept Stat Measurement Theory & Informat Technol, NL-9712 TS
Groningen, Netherlands
Publisher:
PSYCHOMETRIC SOC, WILLIAMSBURG
IDS Number:
652UT
ISSN:
0033-3123
de la Torre J, Deng W
Enhancing the performance of a posterior predictive check
J EDUC MEAS 45 (2): 159-177 SUM 2008
Woods CM
Monte Carlo evaluation of two-level logistic regression for assessing person fit
MULTIVAR BEHAV RES 43 (1): 50-76 JAN-MAR 2008
Sensitivity of MRQAP tests to collinearity and autocorrelation conditions
Dekker D, Krackhardt D, Snijders TAB
PSYCHOMETRIKA
72 (4): 563-581 DEC 2007
Abstract:
Multiple regression quadratic assignment procedures (MRQAP) tests are permutation tests for
multiple linear regression model coefficients for data organized in square matrices of
relatedness among n objects. Such a data structure is typical in social network studies, where
variables indicate some type of relation between a given set of actors. We present a new
permutation method (called "double semi-partialing", or DSP) that complements the family of
extant approaches to MRQAP tests. We assess the statistical bias (type I error rate) and
statistical power of the set of five methods, including DSP, across a variety of conditions of
network autocorrelation, of spuriousness (size of confounder effect), and of skewness in the
data. These conditions are explored across three assumed data distributions: normal, gamma,
and negative binomial. We find that the Freedman-Lane method and the DSP method are the
most robust against a wide array of these conditions. We also find that all five methods
perform better if the test statistic is pivotal. Finally, we find limitations of usefulness for
MRQAP tests: All tests degrade under simultaneous conditions of extreme skewness and high
spuriousness for gamma and negative binomial distributions.
Author Keywords:
MRQAP, Mantel tests, permutation tests, social networks, network autocorrelation,
collinearity, dyadic data
KeyWords Plus:
MULTIPLE-REGRESSION, PERMUTATION TESTS, RANDOMIZATION TESTS,
SOCIAL NETWORKS, MARKOV GRAPHS, MANTEL TEST, FRIENDSHIP, MODELS
Addresses:
Dekker D, Erasmus Univ, Inst Econometr, POB 1738, NL-3000 DR Rotterdam, Netherlands
Radboud Univ Nijmegen, Nijmegen, Netherlands
Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
Univ Groningen, NL-9700 AB Groningen, Netherlands
Univ Oxford, Oxford OX1 2JD, England
Publisher:
SPRINGER, NEW YORK
IDS Number:
259YU
ISSN:
0033-3123
Bayesian inference for dynamic social network data
Koskinen JH, Snijders TAB
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
137 (12): 3930-3938 DEC 1 2007
Abstract:
We consider a continuous-time model for the evolution of social networks. A social network
is here conceived as a (di-) graph on a set of vertices, representing actors, and the changes of
interest are creation and disappearance over time of (arcs) edges in the graph. Hence we
model a collection of random edge indicators that are not, in general, independent. We
explicitly model the interdependencies between edge indicators that arise from interaction
between social entities. A Markov chain is defined in terms of an embedded chain with
holding times and transition probabilities. Data are observed at fixed points in time and hence
we are not able to observe the embedded chain directly. Introducing a prior distribution for
the parameters we may implement an MCMC algorithm for exploring the posterior
distribution of the parameters by simulating the evolution of the embedded process between
observations. (c) 2007 Elsevier B.V. All rights reserved.
Author Keywords:
longitudinal social networks, data augmentation, Bayesian inference, random graphs
KeyWords Plus:
POSTERIOR DISTRIBUTIONS, MODEL
Addresses:
Koskinen JH, Univ Melbourne, Dept Psychol, Parkville, Vic 3010, Australia
Univ Melbourne, Dept Psychol, Parkville, Vic 3010, Australia
Stockholm Univ, Dept Stat, S-10691 Stockholm, Sweden
Univ Oxford Nuffield Coll, Oxford OX1 1NF, England
Univ Groningen, Dept Sociol, NL-9700 AB Groningen, Netherlands
Publisher:
ELSEVIER SCIENCE BV, AMSTERDAM
IDS Number:
211UR
ISSN:
0378-3758
Huisman M, Steglich C
Treatment of non-response in longitudinal network studies
SOC NETWORKS 30 (4): 297-308 OCT 2008
Lazega E, Mounier L, Snijders T, et al.
Networks and controversies : on the effect of norms on the dynamics of structures
REV FR SOCIOL 49 (3): 467-+ JUL-SEP 2008
Lonely but not alone: Emotional isolation and social isolation as two distinct dimensions
of loneliness in older people
van Baarsen B, Snijders TAB, Smit JH, van Duijn MAJ
EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT
61 (1): 119-135 FEB 2001
Abstract:
The unidimensional nature of the De Jong-Gierveld Loneliness Scale is investigated. The
internal properties of the scale scores were studied using item response theory, supplemented
by an external validity study. In line with the theory of relational loneliness, the results stress
the significance of distinguishing between emotional loneliness and social loneliness.
KeyWords Plus:
RASCH MODEL, SUPPORT, SCALE
Addresses:
van Baarsen B, Free Univ Amsterdam, Sect Philosophy& Med Eth, Dept Metamed, Van
Boechorststr 7, NL-1081 BT Amsterdam, Netherlands
Free Univ Amsterdam, Sect Philosophy& Med Eth, Dept Metamed, NL-1081 BT Amsterdam,
Netherlands
Univ Groningen, NL-9700 AB Groningen, Netherlands
Publisher:
SAGE PUBLICATIONS INC, THOUSAND OAKS
IDS Number:
391FP
ISSN:
0013-1644
A multilevel network study of the effects of delinquent behavior on friendship evolution
Snijders TAB, Baerveldt C
JOURNAL OF MATHEMATICAL SOCIOLOGY
27 (2-3): 123-151 APR-SEP 2003
Abstract:
A multilevel approach is proposed to the study of the evolution of multiple networks. In this
approach, the basic evolution process is assumed to be the same, while parameter values may
differ between different networks. For the network evolution process, stochastic actororiented models are used, of which the parameters are estimated by Markov chain Monte
Carlo methods. This is applied to the study of effects of delinquent behavior on friendship
formation, a question of long standing in criminology. The evolution of friendship is studied
empirically in 19 school classes. It is concluded that there is evidence for an effect of
similarity in delinquent behavior on friendship evolution. Similarity of the degree of
delinquent behavior has a positive effect on tie formation but also on tie dissolution. The last
result seems to contradict current criminological theories, and deserves further study.
Author Keywords:
actor-oriented model, longitudinal data, social networks, criminology, adolescents
KeyWords Plus:
ADOLESCENT FRIENDSHIPS, ANTISOCIAL-BEHAVIOR, SIMILARITY, ATTITUDES,
MODEL
Addresses:
Snijders TAB, Univ Groningen, ICS, Dept Sociol, Grote Rozenstr 31, NL-9712 TG
Groningen, Netherlands
Univ Groningen, ICS, Dept Sociol, NL-9712 TG Groningen, Netherlands
Univ Utrecht, ICS, Dept Sociol, NL-3584 CS Utrecht, Netherlands
Publisher:
TAYLOR & FRANCIS LTD, ABINGDON
IDS Number:
678TR
ISSN:
0022-250X