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  • 1
    Online Resource
    Online Resource
    SAGE Publications ; 2019
    In:  Personality and Social Psychology Bulletin Vol. 45, No. 1 ( 2019-01), p. 120-132
    In: Personality and Social Psychology Bulletin, SAGE Publications, Vol. 45, No. 1 ( 2019-01), p. 120-132
    Abstract: People sometimes perceive social environments as unpleasantly crowded. Previous work has linked these experiences to incidental factors such as being hungry or hot and to the relevance of the social environment for an individual’s current goals. Here, we demonstrate that crowding perceptions and evaluations also depend on specific, active threats for perceivers. Eight studies test whether infectious disease threats, which are associated with crowded conditions, increase such reactions. Across studies, pathogen threat made dense social environments seem more crowded and generated more negative affect toward these environments. These perceptions and negative feelings were more influenced by pathogen threat relative to other threats of physical danger. Finally, reactions to pathogen threat affected people’s choice of crowded versus uncrowded environments to inhabit. This research suggests that interpretations of social environments depend on the unique threats and opportunities those environments afford to individuals.
    Type of Medium: Online Resource
    ISSN: 0146-1672 , 1552-7433
    RVK:
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2019
    detail.hit.zdb_id: 2047603-6
    detail.hit.zdb_id: 282406-1
    SSG: 5,2
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  • 2
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2024
    In:  Biometrika ( 2024-02-12)
    In: Biometrika, Oxford University Press (OUP), ( 2024-02-12)
    Abstract: Group testing is an effective way to reduce the time and cost associated with conducting large-scale screening for infectious diseases. Benefits are realized through testing pools formed by combining specimens, such as blood or urine, from different individuals. In some studies, individuals are assessed only once and a time-to-event endpoint is recorded, for example, the time until infection. Combining group testing with this type of endpoint results in group-tested current status data (Petito & Jewell, 2016). To analyse these complex data, we propose methods that estimate a proportional hazard regression model based on test outcomes from measuring the pools. A sieve maximum likelihood estimation approach is developed that approximates the cumulative baseline hazard function with a piecewise constant function. To identify the sieve estimator, a computationally efficient expectation-maximization algorithm is derived by using data augmentation. Asymptotic properties of both the parametric and nonparametric components of the sieve estimator are then established by applying modern empirical process theory. Numerical results from simulation studies show that our proposed method performs nominally and has advantages over the corresponding estimation method based on individual testing results. We illustrate our work by analysing a chlamydia dataset collected by the State Hygienic Laboratory at the University of Iowa.
    Type of Medium: Online Resource
    ISSN: 0006-3444 , 1464-3510
    RVK:
    RVK:
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2024
    detail.hit.zdb_id: 1119-8
    detail.hit.zdb_id: 1470319-1
    SSG: 12
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  • 3
    In: Journal of Applied Psychology, American Psychological Association (APA), Vol. 106, No. 8 ( 2021-08), p. 1103-1117
    Type of Medium: Online Resource
    ISSN: 1939-1854 , 0021-9010
    RVK:
    Language: English
    Publisher: American Psychological Association (APA)
    Publication Date: 2021
    detail.hit.zdb_id: 2066529-5
    detail.hit.zdb_id: 219157-X
    SSG: 5,2
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