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Addressing data privacy in matched studies via virtual pooling

Overview of attention for article published in BMC Medical Research Methodology, September 2017
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Title
Addressing data privacy in matched studies via virtual pooling
Published in
BMC Medical Research Methodology, September 2017
DOI 10.1186/s12874-017-0419-0
Pubmed ID
Authors

P. Saha-Chaudhuri, C.R. Weinberg

Abstract

Data confidentiality and shared use of research data are two desirable but sometimes conflicting goals in research with multi-center studies and distributed data. While ideal for straightforward analysis, confidentiality restrictions forbid creation of a single dataset that includes covariate information of all participants. Current approaches such as aggregate data sharing, distributed regression, meta-analysis and score-based methods can have important limitations. We propose a novel application of an existing epidemiologic tool, specimen pooling, to enable confidentiality-preserving analysis of data arising from a matched case-control, multi-center design. Instead of pooling specimens prior to assay, we apply the methodology to virtually pool (aggregate) covariates within nodes. Such virtual pooling retains most of the information used in an analysis with individual data and since individual participant data is not shared externally, within-node virtual pooling preserves data confidentiality. We show that aggregated covariate levels can be used in a conditional logistic regression model to estimate individual-level odds ratios of interest. The parameter estimates from the standard conditional logistic regression are compared to the estimates based on a conditional logistic regression model with aggregated data. The parameter estimates are shown to be similar to those without pooling and to have comparable standard errors and confidence interval coverage. Virtual data pooling can be used to maintain confidentiality of data from multi-center study and can be particularly useful in research with large-scale distributed data.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 28%
Student > Master 3 17%
Student > Bachelor 2 11%
Other 2 11%
Student > Ph. D. Student 1 6%
Other 2 11%
Unknown 3 17%
Readers by discipline Count As %
Medicine and Dentistry 5 28%
Psychology 2 11%
Nursing and Health Professions 2 11%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Computer Science 1 6%
Other 4 22%
Unknown 3 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 September 2017.
All research outputs
#9,395,279
of 11,753,826 outputs
Outputs from BMC Medical Research Methodology
#831
of 998 outputs
Outputs of similar age
#193,993
of 264,637 outputs
Outputs of similar age from BMC Medical Research Methodology
#20
of 27 outputs
Altmetric has tracked 11,753,826 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 998 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.