Biases arising from using linked administrative data for research: A conceptual framework from registration to analysis. | Zendy

Richard Shaw | Zendy; Katie Harron | Zendy; Júlia Moreira Pescarini | Zendy; Elzo Pereira Pinto | Zendy; Andressa Siroky | Zendy; Desmond Campbell | Zendy; Ruth Dundas | Zendy; Maria Yury Ichihara | Zendy; Maurício L. Barreto | Zendy; Srinivasa Vittal Katikireddi | Zendy

Open Access

Biases arising from using linked administrative data for research: A conceptual framework from registration to analysis.

Author(s) -

Richard Shaw,

Katie Harron,

Júlia Moreira Pescarini,

Elzo Pereira Pinto,

Andressa Siroky,

Desmond Campbell,

Ruth Dundas,

Maria Yury Ichihara,

Maurício L. Barreto,

Srinivasa Vittal Katikireddi

Publication year - 2022

Publication title -

international journal for population data science

Language(s) - English

Resource type - Journals

ISSN - 2399-4908

DOI - 10.23889/ijpds.v7i3.1800

Subject(s) - linkage (software) , data science , computer science , metadata , record linkage , coding (social sciences) , conceptual framework , identification (biology) , process (computing) , population , linked data , matching (statistics) , data mining , information retrieval , world wide web , statistics , sociology , gene , operating system , chemistry , biochemistry , social science , semantic web , botany , biology , demography , mathematics

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