A Simplified Monte Carlo Significance Test Procedure

825 indexed citations
published 1968

Impact in

Journal
Journal of the Royal Statistical Society Series B (Statistical Methodology)

In The Last Decade

doi.org/10.1111/j.2517-6161.1968.tb00759.x →

Countries where authors are citing A Simplified Monte Carlo Significance Test Procedure

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Citations

This map shows the geographic impact of A Simplified Monte Carlo Significance Test Procedure. 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 A Simplified Monte Carlo Significance Test Procedure with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A Simplified Monte Carlo Significance Test Procedure more than expected).

Fields of papers citing A Simplified Monte Carlo Significance Test Procedure

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of A Simplified Monte Carlo Significance Test Procedure. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the A Simplified Monte Carlo Significance Test Procedure.

About A Simplified Monte Carlo Significance Test Procedure

This paper, published in 1968, received 825 indexed citations . It is primarily cited by scholars working on Ecology (126 citations), Statistics and Probability (109 citations), Global and Planetary Change (105 citations), Economics and Econometrics (103 citations) and Nature and Landscape Conservation (102 citations). Published in Journal of the Royal Statistical Society Series B (Statistical Methodology).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global 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.

This paper is also available at doi.org/10.1111/j.2517-6161.1968.tb00759.x.

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