Background
Previous studies offer a limited perspective on the dynamic course of distress in cancer patients and their partners, owing to a restricted number of assessment points and the absence of ...comparison controls drawn from the general population.
Purpose
This study investigated the course of distress among breast cancer patients and their partners (
N
= 92 couples) in comparison to matched control couples (
N
= 64). Furthermore, the influence of neuroticism on distress was investigated.
Method
The Hospital Anxiety and Depression Scale was administered nine times over a 12-month period, and neuroticism was assessed at the beginning of the study using the Eysenck Personality Questionnaire.
Results
Multilevel analyses revealed that patients were more distressed during the first 15 months after diagnosis than nonpatients. A significant portion of the distress that could not be explained by the cancer experience was explained by neuroticism.
Conclusion
Differences in distress between patients and comparison-control women are relatively small and decreased over time, while distress in male partners was not elevated in comparison to their controls.
Comments on Christoph Stadtfeld, James Hollway and Per Block's article Dynamic Network Actor Models: Investigating Coordination Ties through Time (same journal issue).
This study investigated if and how children and teachers differ in their assessment of victim‐aggressor relationships in kindergartens. Self‐, peer, and teacher reports of victimization‐aggression ...networks (who is victimized by whom) were investigated in 25 Swiss kindergartens with 402 5‐ to 7‐years‐old. It was examined whether child characteristics (sex and parent‐reported internalizing and externalizing behavior) influence informant reports of victimization and/or aggression. Findings from statistical network models indicated higher concordance between self and peer reports than between one of these and teacher reports. Results further showed more agreement among informants on aggressors than on victims. Aggressors reported by self and peer reports were low on internalizing behavior, and aggressors reported by self and teacher reports were high on externalizing behavior; teacher‐reported victims were also high on externalizing behavior. Internalizing behavior was unrelated to victimization. According to self and peer reports, boys as well as girls were victimized by boys and girls equally; teachers reported less cross‐sex victimization than same‐sex victimization. The different views of teachers and children on victim‐aggressor relationships have implications for the identification of aggression in early childhood. Mutual sharing of information between children, their parents, peers, and teachers may contribute to signaling victims and aggressors in the early school years.
► General like, general dislike, and bullying relations were studied in 18 classrooms. ► Positive and negative network structures differ systematically in univariate models. ► General dislike and ...bullying are negative networks with different structures. ► Multiplex networks give insight into interdependence of positive-negative relations. ► Children with an equivalent position in the negative network are tied positively.
Three relations between elementary school children were investigated: networks of general dislike and bullying were related to networks of general like. These were modeled using multivariate cross-sectional (statistical) network models. Exponential random graph models for a sample of 18 classrooms, numbering 393 students, were summarized using meta-analyses. Results showed (balanced) network structures with positive ties between those who were structurally equivalent in the negative network. Moreover, essential structural parameters for the univariate network structure of positive (general like) and negative (general dislike and bullying) tie networks were identified. Different structures emerged in positive and negative networks. The results provide a starting point for further theoretical and (multiplex) empirical research about negative ties and their interplay with positive ties.
The Handbook of Rational Choice Social Research offers the first comprehensive overview of how the rational choice paradigm can inform empirical research within the social sciences. This landmark ...collection highlights successful empirical applications across a broad array of disciplines, including sociology, political science, economics, history, and psychology.Taking on issues ranging from financial markets and terrorism to immigration, race relations, and emotions, and a huge variety of other phenomena, rational choice proves a useful tool for theory- driven social research. Each chapter uses a rational choice framework to elaborate on testable hypotheses and then apply this to empirical research, including experimental research, survey studies, ethnographies, and historical investigations. Useful to students and scholars across the social sciences, this handbook will reinvigorate discussions about the utility and versatility of the rational choice approach, its key assumptions, and tools.
We give a nontechnical introduction into
recently developed methods for analyzing the coevolution of social networks and
behavior(s) of the network actors. This coevolution is crucial for a
variety ...of research topics that currently receive a lot of attention, such as
the role of peer groups in adolescent development. A family of dynamic
actor-driven models for the coevolution process is sketched, and it is
shown how to use the SIENA software for estimating these models. We illustrate
the method by analyzing the coevolution of friendship networks, taste in music,
and alcohol consumption of teenagers.
This paper proposes that common measures for network transitivity, based on the enumeration of transitive triples, do not reflect the theoretical statements about transitivity they aim to describe. ...These statements are often formulated as comparative conditional probabilities, but these are not directly reflected by simple functions of enumerations. We think that a better approach is obtained by considering the probability of a tie between two randomly drawn nodes, conditional on selected features of the network. Two measures of transitivity based on correlation coefficients between the existence of a tie and the existence, or the number, of two-paths between the nodes are developed, and called “Transitivity Phi” and “Transitivity Correlation.” Some desirable properties for these measures are studied and compared to existing clustering coefficients, in both random (Erdös–Renyi) and in stylized networks (windmills). Furthermore, it is shown that in a directed graph, under the condition of zero Transitivity Correlation, the total number of transitive triples is determined by four underlying features: size, density, reciprocity, and the covariance between in- and outdegrees. Also, it is demonstrated that plotting conditional probability of ties, given the number of two-paths, provides valuable insights into empirical regularities and irregularities of transitivity patterns.
Multilevel Analysis Tom A B Snijders, Roel J Bosker
2011, 2012., 2011-10-30
eBook
The Second Edition of this classic text introduces the main methods, techniques and issues involved in carrying out multilevel modeling and analysis. Snijders and Bosker?s book is an applied, ...authoritative and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis. This book provides step-by-step coverage of: • multilevel theories • ecological fallacies • the hierarchical linear model • testing and model specification • heteroscedasticity • study designs • longitudinal data • multivariate multilevel models • discrete dependent variables There are also new chapters on: • missing data • multilevel modeling and survey weights • Bayesian and MCMC estimation and latent-class models. This book has been comprehensively revised and updated since the last edition, and now discusses modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and SuperMix. This is a must-have text for any student, teacher or researcher with an interest in conducting or understanding multilevel analysis. Tom A.B. Snijders is Professor of Statistics in the Social Sciences at the University of Oxford and Professor of Statistics and Methodology at the University of Groningen. Roel J. Bosker is Professor of Education and Director of GION, Groningen Institute for Educational Research, at the University of Groningen.
This paper explores time heterogeneity in stochastic actor oriented models (SAOM) proposed by Snijders (Sociological methodology. Blackwell, Boston, pp 361–395,
2001
) which are meant to study the ...evolution of networks. SAOMs model social networks as directed graphs with nodes representing people, organizations, etc., and dichotomous relations representing underlying relationships of friendship, advice, etc. We illustrate several reasons why heterogeneity should be statistically tested and provide a fast, convenient method for assessment and model correction. SAOMs provide a flexible framework for network dynamics which allow a researcher to test selection, influence, behavioral, and structural properties in network data over time. We show how the forward-selecting, score type test proposed by Schweinberger (Chapter 4: Statistical modeling of network panel data: goodness of fit. PhD thesis, University of Groningen
2007
) can be employed to quickly assess heterogeneity at almost no additional computational cost. One step estimates are used to assess the magnitude of the heterogeneity. Simulation studies are conducted to support the validity of this approach. The ASSIST dataset (Campbell et al. In Lancet 371(9624):1595–1602,
2008
) is reanalyzed with the score type test, one step estimators, and a full estimation for illustration. These tools are implemented in the RSiena package, and a brief walkthrough is provided.
For exponential random graph models, under quite general conditions, it is proved that induced subgraphs on node sets disconnected from the other nodes still have distributions from an exponential ...random graph model. This can help in the theoretical interpretation of such models. An application is that for saturated snowball samples from a potentially larger graph which is a realization of an exponential random graph model, it is possible to do the analysis of the observed snowball sample within the framework of exponential random graph models without any knowledge of the larger graph.
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