Feature ArticlesIncremental Effect of Academic Predictors on Nursing Admission AssessmentLiu, Xin PhD; Codd, Casey PhD; Mills, Christine PhDAuthor Information Author Affiliations: Senior Psychometrician (Dr Liu), Lead Psychometrician (Dr Codd), and Director (Dr Mills), Research and Applied Psychometrics, Ascend Learning, Leawood, Kansas. The authors are employed by Ascend Learning, whose subsidiary (Assessment Technologies Institute) produces the assessments discussed in this manuscript. The authors’ compensation is not dependent on research findings. Research design, analysis, and results reporting are conducted independently from the business unit. Correspondence: Dr Liu, 11161 Overbrook Rd, Leawood, KS 66211 (Xin.Liu@AscendLearning.com). Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.nurseeducatoronline.com). Accepted for publication: November 16, 2017 Published ahead of print: December 29, 2017 Nurse Educator: 11/12 2018 - Volume 43 - Issue 6 - p 292-296 doi: 10.1097/NNE.0000000000000502 Buy SDC Metrics Abstract This study examined the incremental values of academic predictors that may be adopted as nursing school admission criteria. The findings revealed that using additional content areas of mathematics, reading, and English in conjunction with science contributes significantly to the prediction of early nursing school success. This study demonstrates an incremental validity approach that provides valuable guidelines to inform the selection of effective, accurate, and cost-effective admission tools for screening qualified nursing candidates. Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.