Statistical Methods for Rates and Proportions.1973 · 1.3k citations
What are hit papers?
Paper score: A paper's citations measured against the top-1% bar of its own field and year: the square root of citations ÷ bar, so 1 means right at the bar and 2 means four times its citations. The bar blends the citation counts that enter the top 1% of the paper's subfields in its year (weighted 89.5%), of those subfields over all years (0.5%) and of its year across all fields (10%); a subfield and year with fewer than 400 papers takes its year's bar. Papers from 2026 are not scored yet: in an unfinished year, when a paper appeared matters more than how it is cited.
Hit paper: A paper cited at least 1.5× the top-1% bar of its field and year: a paper score of at least √1.5.
1973Biometrics
Peers
F. N. D.
Comparison fields: 5 of 168
Statistics and Probability140
Statistics, Probability and Uncertainty53
Demography46
Public Health, Environmental and Occupational Health125
This map shows the geographic impact of F. N. D.'s research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by F. N. D. with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites F. N. D. more than expected).
This network shows the impact of papers produced by F. N. D.. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by F. N. D.. The network helps show where F. N. D. may publish in the future.
Co-authors
The 6 scholars most cited alongside F. N. D., linked wherever they
have co-authored with each other. Click a name or a connecting line to browse the papers
they share.
Border = papers with F. N. D.Line = papers co-authored togetherF. N. D. links everyone, so they are left out of the graph.
F. N. D. is a scholar working on Statistics and Probability, Demography, Theoretical Computer Science, History and Philosophy of Science and Archeology, having authored 9 papers that have together received 1.4k indexed citations. Recurring topics across this work include Probability and Statistical Research (5 papers), Statistical Methods and Applications (4 papers), Insurance, Mortality, Demography, Risk Management (2 papers), Statistics Education and Methodologies (2 papers), History and Theory of Mathematics (1 paper), Statistical Methods and Bayesian Inference (1 paper), Quality of Life Measurement (1 paper) and Mathematical and Theoretical Epidemiology and Ecology Models (1 paper). The work is most often cited by research in Statistics and Probability (140 citations), Statistics, Probability and Uncertainty (53 citations), Demography (46 citations), Public Health, Environmental and Occupational Health (125 citations) and Internal Medicine (10 citations). Frequent co-authors include John H. Pollard, Walter T. Fédérer, Kali S. Banerjee, Ronald Aylmer Fisher, Jon Phillips and Jerzy Neyman. Their work appears in journals such as Biometrics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
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research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.