Use of statistical analysis in the biomedical informatics literature

Abstract

Statistics is an essential aspect of biomedical informatics. To examine the use of statistics in informatics research, a literature review of recent articles in two high-impact factor biomedical informatics journals, the Journal of American Medical Informatics Association (JAMIA) and the International Journal of Medical Informatics was conducted. The use of statistical methods in each paper was examined. Articles of original investigations from 2000 to 2007 were reviewed. For each journal, the results by statistical methods were analyzed as: descriptive, elementary, multivariable, other regression, machine learning, and other statistics. For both journals, descriptive statistics were most often used. Elementary statistics such as t tests, chi(2), and Wilcoxon tests were much more frequent in JAMIA, while machine learning approaches such as decision trees and support vector machines were similar in occurrence across the journals. Also, the use of diagnostic statistics such as sensitivity, specificity, precision, and recall, was more frequent in JAMIA. These results highlight the use of statistics in informatics and the need for biomedical informatics scientists to have, as a minimum, proficiency in descriptive and elementary statistics.