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Jon Heron

ResearcherPublications, citations & collaboration network

Jon Heron is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 574 works, 31,399 citations, an h-index of 87 and an i10-index of 328.

574
Works
31,399
Citations
87
h-index
328
i10-index

How has Jon Heron's publication output changed over time?

ScholarIQpublication output · 2001–2021

Output grew0% over the shown period — from 1 works in 2001 to 1 in 2021.

1
1
2
1
1
1
3
1
20012002200320082010201320192021

What are the most-cited papers on Jon Heron?

ScholarIQmost cited works
Cohort study of depressed mood during pregnancy and after childbirth
Jonathan Evans, Jon Heron, H. Francomb, S. Oke, Jean Golding
BMJ. 20011,297 CitationsOPEN ACCESS
Mendelian randomisation for mediation analysis: current methods and challenges for implementation
Alice R Carter, Eleanor Sanderson, Gemma Hammerton, Rebecca C. Richmond, George Davey Smith, Jon Heron, Amy E. Taylor, Neil M Davies, Laura D Howe
European Journal of Epidemiology. 20211,249 CitationsOPEN ACCESS
The course of anxiety and depression through pregnancy and the postpartum in a community sample
Jon Heron, Thomas G. O’Connor, Jonathan Evans, Jean Golding, Vivette Glover
Journal of Affective Disorders. 20031,161 Citations
The proportion of missing data should not be used to guide decisions on multiple imputation
Paul Madley‐Dowd, Rachael A. Hughes, Kate Tilling, Jon Heron
Journal of Clinical Epidemiology. 20191,066 CitationsOPEN ACCESS
Accounting for missing data in statistical analyses: multiple imputation is not always the answer
Rachael A. Hughes, Jon Heron, Jonathan A C Sterne, Kate Tilling
International Journal of Epidemiology. 2019824 CitationsOPEN ACCESS

Related on ScholarIQ

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Institution
Cohort study of depressed mood during pregnancy and after childbirth
Paper
Mendelian randomisation for mediation analysis: current methods and challenges for implementation
Paper
The course of anxiety and depression through pregnancy and the postpartum in a community sample
Paper
The proportion of missing data should not be used to guide decisions on multiple imputation
Paper
Accounting for missing data in statistical analyses: multiple imputation is not always the answer
Paper
470M+ articles · free account