ArticlePsychological methods2018
Multi-relational measurement for latent construct networks.
Article in Psychological methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Multiple approaches to enhancing cancer communication in the next decade: translating research into practice and policy.Translational behavioral medicine · 2021Article
- The structure of emotional support networks in families affected by Lynch syndrome.Network science (Cambridge University Press) · 2020Article
- Exponential-Family Random Graph Models for Multi-Layer Networks.Psychometrika · 2020Article
- Developing Shared Appraisals of Diabetes Risk Through Family Health History Feedback: The Case of Mexican-Heritage Families.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2018Article
- Interpersonal Correlates of Dementia Caregivers' Emotional Support Networks: Considering Family History.Research on agingArticle
Corrections and comments
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Authors and funding
2 authors.
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Abstract
Multiple item scales have long been used to measure latent constructs on individual-level data. This is appropriate when an otherwise unobserved construct is indirectly measured by combining observable correlated characteristics that are thought to measure slightly different dimensions of that construct. Network data, which consist of observations on the relationships between a set of actors, however, are typically drawn from single-relation measurements. While this approach is sufficient for learning about discrete relations (communication, coauthorship, etc.), multi-item measurement of extemporaneous valued relationships, such as cohesion and conflict, may be of common interest in psychology and related sciences. In this article, we evaluate the use of multirelational network measurement in inferring valued latent construct networks. In particular, we present a psychometric framework for developing multirelational measures of latent construct networks, evaluating their reliability and construct validity, and identification of appropriate scaling approaches for these construct-level networks. (PsycINFO Database Record
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