Scott Morris, PhD
Associate DeanProfessor
Office: Life Sciences Building, Room 248B
Office Hours:
Phone: 312.567.5932
Fax: 312.567.3493
Email:
scott.morris@iit.edu
Web:
Dr. Morris' Lab
Dr. Scott Morris received a Ph.D. in Industrial-Organizational Psychology in 1994 from the University of Akron. He received a B.A. in Psychology from the University of Northern Iowa in 1987.
Dr. Morris teaches courses in personnel selection, covering topics such as job analysis, test development and validation, and legal issues. He also teaches courses in basic and multivariate statistics and multilevel data analysis.
Dr. Morris is actively involved in research on applied statistics and personnel selection. Much of his work involves the development of statistical methods. This includes methods of meta-analysis for program evaluation research, statistics for assessing the adverse impact of employee selection systems, and methods to evaluate the measurement equivalence of questionnaires. He also conducts research exploring issues of validity and discrimination in employee selection systems.
Dr. Morris teaches courses in personnel selection, covering topics such as job analysis, test development and validation, and legal issues. He also teaches courses in basic and multivariate statistics and multilevel data analysis.
Dr. Morris is actively involved in research on applied statistics and personnel selection. Much of his work involves the development of statistical methods. This includes methods of meta-analysis for program evaluation research, statistics for assessing the adverse impact of employee selection systems, and methods to evaluate the measurement equivalence of questionnaires. He also conducts research exploring issues of validity and discrimination in employee selection systems.
Expertise
Education
- Ph.D., University of Akron, 1994
Research & Major Accomplishments
Design of employee selection systems; bias and discrimination in employment decisions, adverse impact analysis; meta-analysis of program evaluation research; differential item functioning and measurement equivalence