Scientific Research on Binary Logistic Regression: A Bibliometric Analysis Using Scopus Data (1974-2024) - Llinás, Humberto (2026)
This study conducts a comprehensive bibliometric analysis of binary logistic regression research spanning from 1974 to 2024. It examines 15,409 documents authored by 77,557 researchers across 137 countries and published in 4,669 different sources. The results reveal a strong and sustained annual growth rate of publications, with a marked surge after 2010, and a global shift toward interdisciplinary applications. China leads in volume of publications (10,553 articles), while the United Kingdom and the Netherlands demonstrate the highest citation impact (approx. 23.5 citations per article). Ethiopia emerges as a notable contributor from the Global South, with more than 8,000 publications. At the journal level, PLOS One and BMC Public Health stand out as the most prolific outlets, whereas the works of Hosmer and Lemeshow remain the most influential references in the field. Thematic mapping highlights clusters in public health, epidemiology, and artificial intelligence, underscoring the central role of binary logistic regression in both methodological and applied domains. These findings provide a panoramic view of the field, highlighting key contributors, trends, and opportunities for future research. The analysis was performed using R-4.4.1 and VOSviewer 1.6.20 software.