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Statistical Methods in Epidemiology
TopicLeading institutions, researchers & key papers
This cluster of papers focuses on various methodological aspects of sample size calculation, logistic regression, predictive modeling, and epidemiologic research. It addresses issues such as sparse data bias, measurement error, risk factors identification, and statistical analysis in clinical studies.
46
Works
IDs:OpenAlex
How has Statistical Methods in Epidemiology's publication output changed over time?
ScholarIQpublication output · 2001–2024
Output grew0% over the shown period — from 1 works in 2001 to 1 in 2024.
1
1
1
1
2001200620232024
What are the most-cited papers on Statistical Methods in Epidemiology?
ScholarIQmost cited works
The Inconsistency of “Optimal” Cutpoints Obtained using Two Criteria based on the Receiver Operating Characteristic Curve
Neil J. Perkins, Enrique F. Schisterman
American Journal of Epidemiology. 20061,769 CitationsOPEN ACCESS
Quantifying possible bias in clinical and epidemiological studies with quantitative bias analysis: common approaches and limitations
Jeremy Brown, Jacob N. Hunnicutt, M. Sanni Ali, Krishnan Bhaskaran, Ashley L. Cole, Sinéad Langan, Dorothea Nitsch, Christopher T. Rentsch, N. W. Galwey, Kevin Wing, Ian Douglas
BMJ. 202443 CitationsOPEN ACCESS
Child and Maternal Mortality Risk Factor Analysis Using Machine Learning Approaches
Md. Alif Sheakh, Mst. Sazia Tahosin, Md Maruf Hasan, Taminul Islam, O. Islam, Md Masum Rana
202329 Citations
Where is Statistical Methods in Epidemiology research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock
How much of the research on Statistical Methods in Epidemiology is open access?
ScholarIQopen access share
75%OPEN ACCESS
Gold
0%
Green
0%
Hybrid
0%
Bronze
75%
Closed
25%
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The Inconsistency of “Optimal” Cutpoints Obtained using Two Criteria based on the Receiver Operating Characteristic Curve
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The use of clinical risk factors enhances the performance of BMD in the prediction of hip and osteoporotic fractures in men and women
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Competing risks in epidemiology: possibilities and pitfalls
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