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Synthesizing external aggregated information in the presence of population heterogeneity: A penalize...

Synthesizing external aggregated information in the presence of population heterogeneity: A penalize...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2485516712

Synthesizing external aggregated information in the presence of population heterogeneity: A penalized empirical likelihood approach

About this item

Full title

Synthesizing external aggregated information in the presence of population heterogeneity: A penalized empirical likelihood approach

Publisher

United States: Blackwell Publishing Ltd

Journal title

Biometrics, 2022-06, Vol.78 (2), p.679-690

Language

English

Formats

Publication information

Publisher

United States: Blackwell Publishing Ltd

More information

Scope and Contents

Contents

With the increasing availability of data in the public domain, there has been a growing interest in exploiting information from external sources to improve the analysis of smaller scale studies. An emerging challenge in the era of big data is that the subject‐level data are high dimensional, but the external information is at an aggregate level and...

Alternative Titles

Full title

Synthesizing external aggregated information in the presence of population heterogeneity: A penalized empirical likelihood approach

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_miscellaneous_2485516712

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2485516712

Other Identifiers

ISSN

0006-341X

E-ISSN

1541-0420

DOI

10.1111/biom.13429

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