Conditioning Diagnostics: Collinearity and Weak Data in Regression

Abstract

loading...

About

This paper, published in 1950, received 729 indexed citations. Written by Richard Goldstein and David A. Belsley covering the research area of . It is primarily cited by scholars working on Economics and Econometrics (105 citations), Statistics and Probability (93 citations) and Strategy and Management (92 citations). Published in Technometrics.

In The Last Decade

doi.org/10.2307/1269293 →

Countries where authors are citing Conditioning Diagnostics: Collinearity and Weak Data in Regression

Since Specialization
Citations

This map shows the geographic impact of Conditioning Diagnostics: Collinearity and Weak Data in Regression. 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 Conditioning Diagnostics: Collinearity and Weak Data in Regression with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Conditioning Diagnostics: Collinearity and Weak Data in Regression more than expected).

Fields of papers citing Conditioning Diagnostics: Collinearity and Weak Data in Regression

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Conditioning Diagnostics: Collinearity and Weak Data in Regression. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Conditioning Diagnostics: Collinearity and Weak Data in Regression.

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/10.2307/1269293.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026