Evidence map›Paper›PMID 31456909›Full record

ArticleSpatial statistics2019

Social Network Spatial Model.

Joseph T Ciminelli, Tanzy Love, Tong Tong Wu

Abstract read
In one paragraph

Article in Spatial statistics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Joseph T CiminelliUniversity of Rochester, 500 Joseph Wilson Boulevard, RC Box 270138, Rochester, NY 14623.
Tanzy LoveUniversity of Rochester, 265 Crittenden Boulevard, Box 630, Rochester, NY 14642.
Tong Tong WuUniversity of Rochester, 265 Crittenden Boulevard, Box 630, Rochester, NY 14642.

Funding

VISUAL INDICES OF NEUROTOXICITYP30ES001247 · NIEHS · UNIVERSITY OF ROCHESTER · PI Martha Susiarjo · 1985 to 2026
$42.8M
Virology/Immunology CoreP30AI078498 · NIAID · UNIVERSITY OF ROCHESTER · PI DEWHURST, STEPHEN · 2008 to 2018
$14.6M
Genetics, Mechanisms and Clinical Phenotypes of Arrhythmogenic CardiomyopathyR01HL116906 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI MARCUS, FRANK I, MESTRONI, LUISA · 2013 to 2016
$9.2M
Trajectories of Physical Activity and Sedentary Time in Adolescent/Young WomenR01HL119058 · NHLBI · KAISER FOUNDATION RESEARCH INSTITUTE · PI YOUNG, DEBORAH R. · 2014 to 2016
$1.9M
Adolescent Physical Activity Decline In GirlsR01HL094572 · NHLBI · UNIV OF MARYLAND, COLLEGE PARK · PI YOUNG, DEBORAH R. · 2009 to 2010
$1.1M
NHLBI NIH HHS R01 HL094572NHLBI NIH HHS R01 HL116906NHLBI NIH HHS R01 HL119058NIAID NIH HHS P30 AI078498NIEHS NIH HHS P30 ES001247
6 · The paper itself

Abstract

Our work is motivated by a desire to incorporate the vast wealth of social network data into the framework of spatial models. We introduce a method for modeling the spatial correlations that exist over a social network. In particular, we model attributes measured for each member of the network as a continuous process over the social space created by their connections. Our method simultaneously models the unobserved locations of network members in social space and the spatial process that exists over that space based on the observed network connections and nodal attributes. The model is evaluated through simulation studies and applied to the importance ranking for a network of emergency response organizations and the physical activity habits of teenage girls. The introduced methods incorporate network data into the spatial framework, expanding traditional models to include this often relevant source of additional information.

Indexed as

node attributessocial networksocial space

Identifiers

PMID31456909
PMCPMC6711610

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.