Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences.
- Journal
- Journal of the Royal Statistical Society Series A (General)
In The Last Decade
doi.org/10.2307/2344367 →Countries where authors are citing Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences.
This map shows the geographic impact of Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences.. 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 Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences. with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences. more than expected).
Fields of papers citing Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences.
This network shows the impact of Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences.. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences..
About Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences.
This paper, published in 1976, received 915 indexed citations . Written by Harvey Goldstein, Jacob Cohen and Patricia Cohen. It is primarily cited by scholars working on Social Psychology (208 citations), Clinical Psychology (204 citations) and Sociology and Political Science (162 citations). Published in Journal of the Royal Statistical Society Series A (General).
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/10.2307/2344367.