Causal inference in statistics : a primer
Impact in
- Journal
- CERN Document Server (European Organization for Nuclear Research)
In The Last Decade
doi.org/w4567685 →Countries where authors are citing Causal inference in statistics : a primer
This map shows the geographic impact of Causal inference in statistics : a primer. 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 Causal inference in statistics : a primer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Causal inference in statistics : a primer more than expected).
Fields of papers citing Causal inference in statistics : a primer
This network shows the impact of Causal inference in statistics : a primer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Causal inference in statistics : a primer.
About Causal inference in statistics : a primer
This paper, published in 2016, received 873 indexed citations . Written by Judea Pearl, Madelyn Glymour and Nicholas P. Jewell. It is primarily cited by scholars working on Artificial Intelligence (370 citations), Statistics and Probability (155 citations), Computer Vision and Pattern Recognition (133 citations), Sociology and Political Science (74 citations) and Information Systems (62 citations). Published in CERN Document Server (European Organization for Nuclear Research).
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/w4567685.