liu.seSearch for publications in DiVA
Endre søk
Begrens søket
1 - 5 of 5
RefereraExporteraLink til resultatlisten
Permanent link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Treff pr side
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Forfatter A-Ø
  • Forfatter Ø-A
  • Tittel A-Ø
  • Tittel Ø-A
  • Type publikasjon A-Ø
  • Type publikasjon Ø-A
  • Eldste først
  • Nyeste først
  • Skapad (Eldste først)
  • Skapad (Nyeste først)
  • Senast uppdaterad (Eldste først)
  • Senast uppdaterad (Nyeste først)
  • Disputationsdatum (tidligste først)
  • Disputationsdatum (siste først)
  • Standard (Relevans)
  • Forfatter A-Ø
  • Forfatter Ø-A
  • Tittel A-Ø
  • Tittel Ø-A
  • Type publikasjon A-Ø
  • Type publikasjon Ø-A
  • Eldste først
  • Nyeste først
  • Skapad (Eldste først)
  • Skapad (Nyeste først)
  • Senast uppdaterad (Eldste først)
  • Senast uppdaterad (Nyeste først)
  • Disputationsdatum (tidligste først)
  • Disputationsdatum (siste først)
Merk
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 1.
    Bader, Felix
    et al.
    School of Social Sciences, University of Mannheim, Mannheim, Germany.
    Baumeister, Bastian
    Institute of Sociology, University of Leipzig, Leipzig, Germany.
    Berger, Roger
    Institute of Sociology, University of Leipzig, Leipzig, Germany.
    Keuschnigg, Marc
    Linköpings universitet, Institutet för analytisk sociologi, IAS. Linköpings universitet, Filosofiska fakulteten.
    On the Transportability of Laboratory Results2019Inngår i: Sociological Methods & Research, ISSN 0049-1241, E-ISSN 1552-8294Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The “transportability” of laboratory findings to other instances than the original implementation entails the robustness of rates of observed behaviors and estimated treatment effects to changes in the specific research setting and in the sample under study. In four studies based on incentivized games of fairness, trust, and reciprocity, we evaluate (1) the sensitivity of laboratory results to locally recruited student-subject pools, (2) the comparability of behavioral data collected online and, under varying anonymity conditions, in the laboratory, (3) the generalizability of student-based results to the broader population, and (4), with a replication at Amazon Mechanical Turk, the stability of laboratory results across research contexts. For the class of laboratory designs using interactive games as measurement instruments of prosocial behavior we find that rates of behavior and the exact behavioral differences between decision situations do not transport beyond specific implementations. Most clearly, data obtained from standard participant pools differ significantly from those from the broader population. This undermines the use of empirically motivated laboratory studies to establish descriptive parameters of human behavior. Directions of the behavioral differences between games, in contrast, are remarkably robust to changes in samples and settings. Moreover, we find no evidence for either anonymity effects nor mode effects potentially biasing laboratory measurement. These results underscore the capacity of laboratory experiments to establish generalizable causal effects in theory-driven designs.

  • 2.
    Hedström, Peter
    et al.
    Linköpings universitet, Institutionen för samhälls- och välfärdsstudier, Institutet för analytisk sociologi, IAS. Linköpings universitet, Filosofiska fakulteten.
    Manzo, Gianluca
    CNRS, France; University of Paris 04, France.
    Recent Trends in Agent-based Computational Research: A Brief Introduction2015Inngår i: Sociological Methods & Research, ISSN 0049-1241, E-ISSN 1552-8294, Vol. 44, nr 2, s. 179-185Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    n/a

  • 3.
    Manzo, Gianluca
    et al.
    CNRS & University of Paris–Sorbonne, Paris, France.
    Baldassarri, Delia
    New York University, New York, NY, USA.
    Heuristics, Interactions, and Status Hierarchies: An Agent-based Model of Deference Exchange2015Inngår i: Sociological Methods & Research, ISSN 0049-1241, E-ISSN 1552-8294, Vol. 44, nr 2, s. 329-387Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Since Merton’s classical analysis of cumulative advantage in science, it has been observed that status hierarchies display a sizable disconnect between actors’ quality and rank and that they become increasingly asymmetric over time, without, however, turning into winner-take-all structures. In recent years, formal models of status hierarchies tried to account for these facts by combining two micro-level, counterbalancing mechanisms: “social influence” (supposedly driving inequality) and the desire for “reciprocation in deferential gestures” (supposedly limiting inequality). In the article, we adopt as empirical benchmark basic features that are common to most distributions of status indicators (e.g., income, academic prestige, wealth, social ties) and argue that previous formal models were only partially able to reproduce such macro-level patterns. We then introduce a novel agent-based computational model of deferential gestures that improves on the realism of previous models by introducing heuristic-based decision making, actors’ heterogeneity, and status homophily in social interactions. We systematically and extensively study the model’s parameter space and consider a few variants to determine under which conditions the macroscopic patterns of interest are more likely to appear. We find that specific forms of status-based heterogeneity in actors’ propensity to interact with status-dissimilar others are needed to generate status hierarchies that best approximate these macroscopic features.

  • 4.
    Spaiser, Viktoria
    et al.
    School of Politics and International Studies, University of Leeds, Leeds, UK.
    Hedström, Peter
    Linköpings universitet, Institutionen för samhälls- och välfärdsstudier, Institutet för analytisk sociologi, IAS. Linköpings universitet, Filosofiska fakulteten.
    Ranganathan, Shyam
    Department of Mathematics, Uppsala University, Uppsala, Sweden.
    Jansson, Kim
    Linköpings universitet, Institutionen för samhälls- och välfärdsstudier, Institutet för analytisk sociologi, IAS. Linköpings universitet, Filosofiska fakulteten.
    Nordvik, Monica K
    Linköpings universitet, Institutionen för samhälls- och välfärdsstudier, Institutet för analytisk sociologi, IAS. Linköpings universitet, Filosofiska fakulteten.
    Sumpter, David J T
    Department of Mathematics, Uppsala University, Uppsala, Sweden.
    Identifying Complex Dynamics in Social Systems: A New Methodological Approach Applied to Study School Segregation2018Inngår i: Sociological Methods & Research, ISSN 0049-1241, E-ISSN 1552-8294, nr 2, s. 103-135Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    It is widely recognized that segregation processes are often the result of complex nonlinear dynamics. Empirical analyses of complex dynamics are however rare, because there is a lack of appropriate empirical modeling techniques that are capable of capturing complex patterns and nonlinearities. At the same time, we know that many social phenomena display nonlinearities. In this article, we introduce a new modeling tool in order to partly fill this void in the literature. Using data of all secondary schools in Stockholm county during the years 1990 to 2002, we demonstrate how the methodology can be applied to identify complex dynamic patterns like tipping points and multiple phase transitions with respect to segregation. We establish critical thresholds in schools’ ethnic compositions, in general, and in relation to various factors such as school quality and parents’ income, at which the schools are likely to tip and become increasingly segregated.

  • 5.
    Stadtfeld, Christoph
    et al.
    ETH Zurich.
    Snijders, Tom
    University of Groningen.
    Steglich, Christian
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Institutet för analytisk sociologi, IAS. Linköpings universitet, Filosofiska fakulteten.
    van Duijn, Marijtje
    University of Groningen.
    Statistical Power in Longitudinal Network Studies2018Inngår i: Sociological Methods & Research, ISSN 0049-1241, E-ISSN 1552-8294Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Longitudinal social network studies can easily suffer from insufficient statistical power. Studies that simultaneously investigate change of network ties and change of nodal attributes (selection and influence studies) are particularly at risk because the number of nodal observations is typically much lower than the number of observed tie variables. This article presents a simulation-based procedure to evaluate statistical power of longitudinal social network studies in which stochastic actor-oriented models are to be applied. Two detailed case studies illustrate how statistical power is strongly affected by network size, number of data collection waves, effect sizes, missing data, and participant turnover. These issues should thus be explored in the design phase of longitudinal social network studies.

1 - 5 of 5
RefereraExporteraLink til resultatlisten
Permanent link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf