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(PDF) Network Analysis, Longitudinal Methods of
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This two-way influence can be represented by models for the co-evolution of networks and changeable actor attributes. Such models, and statistical methods to analyze panel data on networks and behavior, are also treated. 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const worksViewsPath = "/v0/works/views?subdomain_param=api&work_ids%5B%5D=77853905"; const getWorkViews = async (workId) => { const response = await fetch(worksViewsPath); if (!response.ok) { throw new Error('Failed to load work views'); } const data = await response.json(); return data.views[workId]; }; // Get the view count for the work - we send this immediately rather than waiting for // the DOM to load, so it can be available as soon as possible (but without holding up // the backend or other resource requests, because it's a bit expensive and not critical). const viewCount = await getWorkViews(workId); const updateViewCount = (viewCount) => { try { const viewCountNumber = parseInt(viewCount, 10); if (viewCountNumber === 0) { // Remove the whole views element if there are zero views. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); return; } const commaizedViewCount = viewCountNumber.toLocaleString(); const viewCountBody = document.getElementById('work-metadata-view-count'); if (!viewCountBody) { throw new Error('Failed to find work views element'); } viewCountBody.textContent = `${commaizedViewCount} views`; } catch (error) { // Remove the whole views element if there was some issue parsing. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); throw new Error(`Failed to parse view count: ${viewCount}`, error); } }; // If the DOM is still loading, wait for it to be ready before updating the view count. if (document.readyState === "loading") { document.addEventListener('DOMContentLoaded', () => { updateViewCount(viewCount); }); // Otherwise, just update it immediately. } else { updateViewCount(viewCount); } })();</script></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">Glossary Definition of the Subject havior -and in turn the network ties are influenced by individual behavior. This two-way influence can be represented by models for the co-evolution of networks and changeable actor attributes. Such models, and statistical methods to analyze panel data on networks and behavior, are also treated. An extensive example is discussed about friendship among teenagers in a school setting.</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":85103045,"attachmentType":"pdf","workUrl":"https://www.academia.edu/77853905/Network_Analysis_Longitudinal_Methods_of"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":85103045,"attachmentType":"pdf","workUrl":"https://www.academia.edu/77853905/Network_Analysis_Longitudinal_Methods_of"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div><div class="ds-signup-banner-trigger-container"><div class="ds-signup-banner-trigger ds-signup-banner-trigger-control"></div></div><div class="ds-signup-banner ds-signup-banner-control"><div id="ds-signup-banner-close-button"><button class="ds2-5-button ds2-5-button--secondary ds2-5-button--inverse"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">close</span></button></div><div class="ds-signup-banner-ctas" data-impression-entity-id="77853905" data-impression-entity-type="2" data-impression-source="signup-banner"><img src="//a.academia-assets.com/images/academia-logo-capital-white.svg" /><h4 class="ds2-5-heading-serif-sm">Sign up for access to the world's latest research</h4><button class="ds2-5-button ds2-5-button--inverse ds2-5-button--full-width js-swp-download-button" data-signup-modal="{"location":"signup-banner"}">Sign up for free<span class="material-symbols-outlined" style="font-size: 20px" translate="no">arrow_forward</span></button></div><div class="ds-signup-banner-divider"></div><div class="ds-signup-banner-reasons"><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Get notified about relevant papers</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Save papers to use in your research</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Join the discussion with peers</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Track your impact</span></div></div></div><script>(() => { // Set up signup banner show/hide behavior: // 1. 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Syuzo-takabatake</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Social Network Analysis</p><p class="ds-related-work--abstract ds2-5-body-sm">Actors and their actions are viewed as interdependent rather than independent, autonomous units 0 Relational ties (linkages) between actors are channels for transfer or "flow" of resources (either material or nonmaterial) 0 Network models focusing on individuals view the network structural environment as providing opportunities for or constraints on individual action 0 Network models conceptualize structure (social, economic, political, and so forth) as lasting patterns of relations among actors In this section we discuss these principles further and illustrate how the social network perspective differs from alternative perspectives in practice. Of critical importance for the development of methods for</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Social Network Analysis in the Social and Behavioral Sciences","attachmentId":116098446,"attachmentType":"pdf","work_url":"https://www.academia.edu/121136471/Social_Network_Analysis_in_the_Social_and_Behavioral_Sciences","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/121136471/Social_Network_Analysis_in_the_Social_and_Behavioral_Sciences"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="77853962" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/77853962/Multilevel_Longitudinal_Analysis_of_Social_Networks">Multilevel Longitudinal Analysis of Social Networks</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="27849710" href="https://independent.academia.edu/TomSnijders">Tom Snijders</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2022</p><p class="ds-related-work--abstract ds2-5-body-sm">Stochastic actor-oriented models (SAOM) are a broadly applied modelling framework for analysing network dynamics using network panel data. They have been extended to address co-evolution of multiple networks as well as networks and behaviour. This paper extends the SAOM to the analysis of multiple network panels through a random coefficient multilevel model, estimated with a Bayesian approach. This is illustrated by a study of the dynamic interdependence of friendship and minor delinquency, represented by the combination of a one-mode and a two-mode network, using a sample of 81 school classes in the first year of secondary school.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Multilevel Longitudinal Analysis of Social Networks","attachmentId":85103067,"attachmentType":"pdf","work_url":"https://www.academia.edu/77853962/Multilevel_Longitudinal_Analysis_of_Social_Networks","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/77853962/Multilevel_Longitudinal_Analysis_of_Social_Networks"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="18945562" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/18945562/Modeling_the_co_evolution_of_networks_and_behavior_Chapter_3_in_K_van_Montfort_H_Oud_and_A_Satorra_Eds_Longitudinal_models_in_the_behavioral_and_">Modeling the co-evolution of networks and behavior. Chapter 3 in K. van Montfort, H. Oud and A. Satorra (Eds.): Longitudinal models in the behavioral and …</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="27849710" href="https://independent.academia.edu/TomSnijders">Tom Snijders</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2007</p><p class="ds-related-work--abstract ds2-5-body-sm">A deeper understanding of the relation between individual behavior and individual actions on one hand and the embeddedness of individuals in social structures on the other hand can be obtained by empirically studying the dynamics of individual outcomes and network structure, and how these mutually affect each other. In methodological terms, this means that behavior of individuals -indicators of performance and success, attitudes and other cognitions, behavioral tendencies -and the ties between them are studied as a social process evolving over time, where behavior and network ties mutually influence each other. We propose a statistical methodology for this type of investigation and illustrate it by an example. * We thank the Chief Scientists Office of the Scottish Home and Health Department for permission to use the data of the Teenage Friends and Lifestyle Study.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Modeling the co-evolution of networks and behavior. Chapter 3 in K. van Montfort, H. Oud and A. Satorra (Eds.): Longitudinal models in the behavioral and …","attachmentId":40344206,"attachmentType":"pdf","work_url":"https://www.academia.edu/18945562/Modeling_the_co_evolution_of_networks_and_behavior_Chapter_3_in_K_van_Montfort_H_Oud_and_A_Satorra_Eds_Longitudinal_models_in_the_behavioral_and_","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/18945562/Modeling_the_co_evolution_of_networks_and_behavior_Chapter_3_in_K_van_Montfort_H_Oud_and_A_Satorra_Eds_Longitudinal_models_in_the_behavioral_and_"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="11476390" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/11476390/Network_behavior_dynamics">Network-behavior dynamics</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="27952734" href="https://rug.academia.edu/CSteglich">Christian E G Steglich</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2013</p><p class="ds-related-work--abstract ds2-5-body-sm">Researchers have become increasingly interested in disentangling selection and influence processes. This literature review provides context for the special issue on network-behavior dynamics. It brings together important conceptual, methodological, and empirical contributions focusing on longitudinal social network modeling. First, an overview of mechanisms underlying selection and influence is given. After a description of the shortcomings of previous studies in this area, the stochastic actor-based model is sketched; this is used in this special issue to examine network-behavior dynamics. The preconditions for such analyses are discussed, as are common model specification issues. Next, recent empirical advances in research on adolescence are discussed, focusing on new insights into moderating effects, initiation of behaviors, time heterogeneity, mediation effects, and negative ties.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Network-behavior dynamics","attachmentId":46685792,"attachmentType":"pdf","work_url":"https://www.academia.edu/11476390/Network_behavior_dynamics","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/11476390/Network_behavior_dynamics"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="121136463" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/121136463/Longitudinal_analysis_of_friendship_networks">Longitudinal analysis of friendship networks</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="36922571" href="https://independent.academia.edu/ASyuzotakabatake">A. Syuzo-takabatake</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Social Networks, 1979</p><p class="ds-related-work--abstract ds2-5-body-sm">This note discusses and demonstrates methods, both exploratory and confirmatory, for analyzing data from friendship networks collected over time. The focus is on stochastic models for dyadic interaction designed to quantify the structural effect of reciprocity on arc changes. The networks studied were previously analyzed by Hallinan (Social Networks, 1:193-210) who was concerned with_ stability of dyadic choices and the direction of change of asymmetric dyads to either mutual or null dyads. These aspects of the networks are really of secondary importance to the effect of reciprocated choices on the probabilities of dyadic change. Measures of this "reciprocity effect"-are presented, and connnents on the rationale for continuous-time Markov chains as models for networks are given.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Longitudinal analysis of friendship networks","attachmentId":116098439,"attachmentType":"pdf","work_url":"https://www.academia.edu/121136463/Longitudinal_analysis_of_friendship_networks","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/121136463/Longitudinal_analysis_of_friendship_networks"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="16916173" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/16916173/Network_Analysis_in_the_Social_Sciences">Network Analysis in the Social Sciences</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="36820590" href="https://independent.academia.edu/DBrass1">D. Brass</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="36411946" href="https://uky.academia.edu/GiuseppeLabianca">Giuseppe Labianca</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Science, 2009</p><p class="ds-related-work--abstract ds2-5-body-sm">The following resources related to this article are available online at</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Network Analysis in the Social Sciences","attachmentId":39256013,"attachmentType":"pdf","work_url":"https://www.academia.edu/16916173/Network_Analysis_in_the_Social_Sciences","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/16916173/Network_Analysis_in_the_Social_Sciences"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="18050853" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/18050853/Variations_in_network_boundary_and_type_A_study_of_adolescent_peer_influences">Variations in network boundary and type: A study of adolescent peer influences</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="37993168" href="https://independent.academia.edu/DaniellaMeeker">Daniella Meeker</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Social Networks, 2013</p><p class="ds-related-work--abstract ds2-5-body-sm">This study compares variation in network boundary and network type on network indicators such as degree and estimates of social influences on adolescent substance use. We compare associations between individual use and peer use of tobacco and alcohol when network boundary (e.g., classroom, entire grade in school, and community) and relational type (elicited by asking whom students: (a) are friends with, (b) admire, (c) think will succeed, (d) would like to have a romantic relationship with, and (e) think are popular) are varied. Additionally, we estimate Exponential Random Graph Models (ERGMs) for 232 networks to obtain a homophily estimate for smoking and drinking. Data were collected from a crosssectional sample of 1707 adolescents in five high schools in one school district in Los Angeles, CA. Results of logistic regression models show that associations were strongest when the boundary condition was least constrained and that associations were stronger for friendship networks than for other ones. Additionally, ERGM estimations show that grade-level friendship networks returned significant homophily effects more frequently than the classroom networks. This study validates existing theoretical approaches to the network study of social influence as well as ways to estimate them. We recommend researchers use as broad a boundary as possible when collecting network data, but observe that for some research purposes more narrow boundaries may be preferred.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Variations in network boundary and type: A study of adolescent peer influences","attachmentId":39849234,"attachmentType":"pdf","work_url":"https://www.academia.edu/18050853/Variations_in_network_boundary_and_type_A_study_of_adolescent_peer_influences","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/18050853/Variations_in_network_boundary_and_type_A_study_of_adolescent_peer_influences"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="94060468" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/94060468/Network_Ecology_and_Adolescent_Social_Structure">Network Ecology and Adolescent Social Structure</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="154324139" href="https://independent.academia.edu/JamesMoody15">James Moody</a></div><p class="ds-related-work--metadata ds2-5-body-xs">American sociological review, 2014</p><p class="ds-related-work--abstract ds2-5-body-sm">Adolescent societies-whether arising from weak, short-term classroom friendships or from close, long-term friendships-exhibit various levels of network clustering, segregation, and hierarchy. Some are rank-ordered caste systems and others are flat, cliquish worlds. Explaining the source of such structural variation remains a challenge, however, because global network features are generally treated as the agglomeration of micro-level tie-formation mechanisms, namely balance, homophily, and dominance. How do the same micro-mechanisms generate significant variation in global network structures? To answer this question we propose and test a network ecological theory that specifies the ways features of organizational environments moderate the expression of tie-formation processes, thereby generating variability in global network structures across settings. We develop this argument using longitudinal friendship data on schools (Add Health study) and classrooms (Classroom Engagement study)...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Network Ecology and Adolescent Social Structure","attachmentId":96625402,"attachmentType":"pdf","work_url":"https://www.academia.edu/94060468/Network_Ecology_and_Adolescent_Social_Structure","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/94060468/Network_Ecology_and_Adolescent_Social_Structure"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="13503075" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/13503075/Social_Networks_in_the_NSHAP_Study_Rationale_Measurement_and_Preliminary_Findings">Social Networks in the NSHAP Study: Rationale, Measurement, and Preliminary Findings</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="32541702" href="https://chicago.academia.edu/EdwardLaumann">Edward Laumann</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="32705752" href="https://cornell.academia.edu/BenjaminCornwell">Benjamin Cornwell</a></div><p class="ds-related-work--metadata ds2-5-body-xs">The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 2009</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Social Networks in the NSHAP Study: Rationale, Measurement, and Preliminary Findings","attachmentId":45261942,"attachmentType":"pdf","work_url":"https://www.academia.edu/13503075/Social_Networks_in_the_NSHAP_Study_Rationale_Measurement_and_Preliminary_Findings","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/13503075/Social_Networks_in_the_NSHAP_Study_Rationale_Measurement_and_Preliminary_Findings"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="6312789" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/6312789/Multilevel_analysis_of_personal_networks_as_dependent_variables">Multilevel analysis of personal networks as dependent variables</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="9808484" href="https://rug.academia.edu/marijtjevanduijn">marijtje van duijn</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Social Networks, 1999</p><p class="ds-related-work--abstract ds2-5-body-sm">In this paper, it is shown that multilevel methods are particularly well-suited for the analysis of relations in personal networks and the changes in these relations. Justice is done to the hierarchical nested structure of the data and the resulting dependence between observations ''within egos''. Multilevel techniques can also give more specific insight on why personal networks change: they allow to distinguish between the influence of individual and of tie characteristics on the stability of personal networks as a whole and of specific ties within a personal network. This is illustrated by an application to changes in networks of four Dutch samples experiencing different life events. q 1999 Elsevier Science B.V. All rights reserved.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Multilevel analysis of personal networks as dependent variables","attachmentId":48920904,"attachmentType":"pdf","work_url":"https://www.academia.edu/6312789/Multilevel_analysis_of_personal_networks_as_dependent_variables","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/6312789/Multilevel_analysis_of_personal_networks_as_dependent_variables"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":85103045,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":85103045,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_85103045" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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adolescence","attachmentId":40592631,"attachmentType":"pdf","work_url":"https://www.academia.edu/19388343/dynamic_model_of_the_friendship_network_evolution_and_academic_achievement_for_adolescence","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/19388343/dynamic_model_of_the_friendship_network_evolution_and_academic_achievement_for_adolescence"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="8" data-entity-id="3278868" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title 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Elsevier, Academic Press, pp. 745-781., 2005</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Methods of social networks analysis","attachmentId":33245493,"attachmentType":"pdf","work_url":"https://www.academia.edu/3278868/Methods_of_social_networks_analysis","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/3278868/Methods_of_social_networks_analysis"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container 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