Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls2009 · 5.1k citations
What are hit papers?
Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if any of the following hold:
it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the
threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.
Countries citing papers authored by Michael Spratt
Since Specialization
Citations
This map shows the geographic impact of Michael Spratt'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 Michael Spratt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Spratt more than expected).
This network shows the impact of papers produced by Michael Spratt. 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 Michael Spratt. The network helps show where Michael Spratt may publish in the future.
Co-authors
The 19 scholars most cited alongside Michael Spratt, 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 Michael SprattLine = papers co-authored togetherMichael Spratt links everyone, so they are left out of the graph.
All Works
5 of 5 papers shown
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Work
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Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls
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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.