Randall Schumacker

HIGHLIGHTED PUBLICATIONS

Conference Presentations

1. Schumacker, R.E. & Sherron, T. (April 2024).  Difference-in-Differences Regression Model and Comparable Methods.  Linear, Nonlinear, Latent and Machine Learning for Educational Research.  American Educational Research Association, Philadelphia, PA.
2. Papa, F.J., Selby, S., Tierney, N., & Schumacker, R. (May 2024).  Improvements in the Clinical Competencies of year two Medical students trained with a high-fidelity abdominal simulator.  University of Texas Southwestern 7^th Annual Charles Morris Ginsburg Simulation-Based Quality Improvement and Research Conference, Dallas, Texas. https://www.utsouthwestern.edu/departments/simulation-center/.
3. Lugu, B., Ma, W., Guo, W., & Schumacker, R. (2023, April). Cognitive Diagnosis Model for Disengaged Behaviors. National Council on Measurement Education, Chicago, IL.
4. Leithwood, K., Sun, J.-P., Schumacker, R., & Hua, C. (2023, April). Psychometric Properties of the Successful School Leadership Survey.  Educational Leadership SIG. American Educational Research Association, Chicago, Illinois.
5. Schumacker, R.E. & Holmes, L. (2022, April).  Testing Individual vs Group Mean Differences in Social Science Research.  Multiple Linear Regression:  General Linear Model SIG,  American Educational Research Association, San Diego, CA.
6. Schumacker, R.E. (2022, April).  Identifying Number of Curves in Longitudinal Growth Models.  Educational Statistician SIG, American Educational Research Association, San Diego, CA.
7. Wind, S.A. & Schumacker, R.E. (2021, April).  Exploring the Impact of Missing Data on Residual-Based Dimensionality Analysis for Measurement Models.  American Educational Research Association, Orlando, FL.
8. Schumacker, R.E. & Yonghong, Cai (2021, April). Principal Leadership Effect on Teaching:  Does it Matter?  American Educational Research Association, Orlando, FL.
9. Schumacker, R.E. & Holmes, L. (2020, April).  Can We Identify Effective Teachers? Latent Class Analysis of Teacher Characteristics.  American Educational Research Association, San Francisco, CA.
10. Ma, Wenchao, Jiang, Z. & Schumacker, R.E. (2020, April).  Modeling Omitted Items in Cognitive Diagnosis Models. American Educational Research Association, San Francisco, CA.
11. Jiang, Zhehan, Ma, Wenchao, Schumacker, R.E. & Zhang, I.  (2020, April).  Fully-Bayesian Model Selection Methods in Diagnostic Classification Models.  American Educational Research Association, San Francisco, CA.

Publications

1. Raykov, T., Calvorcoressi, L., & Schumacker, R. (2024).  Choosing between the Bi-Factor and Second Order Factor Models:  A direct test using latent variable modeling.  Measurement:  Interdisciplinary Research and Perspectives, 22(1), 31-50.
2. Raykov, T., Marcoulides, G., & Schumacker, R. (2024).  Scale reliability evaluation using Bayesian Analysis: A latent variable procedure.  Measurement:  Interdisciplinary Research and Perspectives, 22(1), 51-60.
3. Huang, X., Schumacker, R.E., Binbin, C., & Chiu, M.M. (2023).  Latent Class Analysis to Identify Parental Involvement Styles in Chinese Children’s Learning at Home.  Behavioral Sciences, 12, 237-249. DOI:  10.3390/bs12070237
4. Gan, Z., He, J., Zhang, L.J. & Schumacker, R.E. (2023).  Examining the Relationships between Feedback Practices and Learning Motivation.  Measurement:  Interdisciplinary Research and Perspectives, 21(1), 38-50.
5. Leithwood, K., Sun, J., Schumacker, R. & Hua, C. (2023).  Psychometric Properties of the Successful School Leadership Survey.   Journal of Educational Administration, 61(4), 385-404.
6. Gan, Z., Zheng, Y. & Schumacker, R. (2023).  Examining the Psychometric Properties of the Motivational Scale of MSLQ for English Learning among Chinese Secondary Students.  Journal of Psychoeducational Assessment, 41(8), 942-951.  https://doi.org/10.1177/07342829231193064
7. Kaiwen, M., Schumacker, R.E., Morell, Monica, Wang, Y.  (2022).  Effects of Compounded Nonnormality of Residuals in Hierarchical Linear Modeling, Educational and Psychological Measurement, 82(2), 330-355. https://doi.org/10.1177/00131644211010234
8. Schumacker, R.E. & Holmes, L.F. (2022).  Testing Individual vs Group Mean Differences in Social Science Research.  General Linear Model Journal, 46(1), 43 – 50.
9. Fye, H. J, Schumacker, R.E., Rainey, S. J., & Guillot Miller, L. (2022). ASCA National Model Implementation Predicting School Counselors’ Job Satisfaction with Role Stress Mediating Variables. Journal of Employment Counseling, 59(2), 1–9. https://doi.org/10.1002/joec.12181
10. Schumacker, R.E., Wind, S.A. & Holmes, L. F.  (2021). Resources for Identifying Measurement Instruments for Social Science Research, Measurement:  Interdisciplinary Research and Perspectives, 19(4), 250-257.

Books

1. Schumacker, R.E. (2023).  Statistics Made Easy.  KD Publishers:  Seattle,  Washington.
2. Schumacker, R.E. (2022).  Multivariate Statistics.  KD Publishers :  Seattle, Washington.
3. Whittaker, T. & Schumacker, R. (2022).  A Beginner’s Guide to Structural Equation Modeling (5^th Edition).  Routledge:  New York, NY.
4. Schumacker, R. E. (2016).  Using R with Multivariate Statistics.  Belmont, CA:  SAGE
5. Schumacker, R. (2015).  Learning Statistics Using R.  Belmont, CA: Sage.
6. Schumacker, R. & Tomek, S. (2013). Understanding Statistics Using R.  New York, NY: Springer Verlag. 
7. Marcoulides, G.A. & Schumacker, R.E. (2001).  Advanced Structural Equation Modeling:   New Developments and Techniques.  Lawrence Erlbaum Associates, Inc.: Mahwah, NJ.
8. Schumacker, R.E. & Marcoulides, G.A. (Eds.) (1998).  Interaction and Nonlinear Effects in Structural Equation Modeling.  Lawrence Erlbaum Associates, Inc.: Mahwah, NJ.

PROFESSIONAL ACTIVITIES

International Workshops

• Schumacker, R.E. (2018).  SEM Models and Applications.  East China Normal University, Shanghai, China.
• Schumacker, R.E. (2018).  Defining Latent Variable Classes.  East China Normal University, Shanghai, China.
• Schumacker, R.E. (2018).  School System Effectiveness.  East China Normal University, Shanghai, China.
• Schumacker, R.E. (2018).  Principal Leadership Studies.  East China Normal University, Shanghai, China.
• Schumacker, R.E. (2018). Multi-level SEM. Nanjing Normal University, Nanjing, China.
• Schumacker, R.E. (2018). Principal Leadership Studies. Nanjing Normal University, Nanjing, China.
• Schumacker, R.E. (2018). Rasch Measurement Models. Nanjing Normal University, Nanjing, China.
• Schumacker, R.E. (2018).  Longitudinal Growth, Mixture, and Latent Transition Analysis.  Beijing Normal University, Beijing, China.
• Schumacker, R.E. (2018).  Multivariate Statistics using R.   Beijing Normal University, Beijing, China.
• Schumacker, R.E. (2018).  SEM Using R.  Beijing Normal University, Beijing, China.
• Schumacker, R.E. (2018). Defining Latent Variables. Beijing Normal University, Beijing, China.
• Schumacker, R.E. (2018).  MIMIC models. Beijing Normal University, Beijing, China.

Community Service (Evaluation and Planning)

• 2019 – Tuscaloosa One’s Place, Tuscaloosa Family Resource Center, Inc.
  
  Juveniles Supported Through Integrated Community Engagement (JUSTICE)
  
  Tuscaloosa’s One Place, A Family Resource Center created the Juveniles Supported Through Integrated Community Engagement (JUSTICE) program to fill the void of juvenile reentry services in Tuscaloosa County. 
  
  The JUSTICE program provided case management, goal mentoring, GED curriculum, legal assistance, grievance counseling, and mental health counseling for 28 juveniles released to the community from July to December 2018.  Individual case narratives reveal each juvenile set of circumstances with a common theme of having the loss of one or more parent, poor home environment, and lack of routine and discipline.  Probability of success in program was highly predictable based on number of days in the program and knowing the number of prior crimes.  Juvenile records were expunged by legal services if successfully completed program. Recommended funding for additional years of JUSTICE program support given effectiveness and low-cost versus the incarceration and detention annual costs for juveniles. 

• 2023 – Community Juvenile Delinquency Prevention Project
  
  Developed the project narrative, budget, and proposal with Tyler Fezzey, doctoral student in College of Business, that was submitted to the Tuscaloosa City Council. The project and budget was fully funded.
  
  Programs and initiatives started by Donnie, Lee Jr., Ivy Foundation,  was designed to reduce juvenile detention recidivism, mentor at-risk youth, and guide them toward college, GED, trade school, and general community re-entry. The programs have already generated great success and have been in regular contact with different constituents like the police department and Tuscaloosa city schools who have issued their support and funding, e.g. gift cards, tutoring after school, and sport activities.

• 2024 – CITI Training  – Non-Medical Human Subjects Certificate

• 2024 – CITI Training  – Conflict of Interest Certificate

BIOGRAPHY

DR. RANDALL E. SCHUMACKER is a Professor of Educational Research at The University of Alabama, where he teaches courses in multiple regression, multivariate statistics and structural equation modeling.  His research interests are varied, including applications in  SEM, psychometrics, and meta-analysis.  He has taught several international and national workshops on structural equation modeling.

Randall has written and co-edited several books, including A Beginner’s Guide to Structural Equation Modeling (5^th edition); Advanced Structural Equation Modeling: Issues and Techniques; Interaction and Non-Linear Effects in Structural Equation Modeling; New Developments and Techniques in Structural Equation Modeling; Understanding Statistical Concepts Using S-PLUS; Understanding Statistics Using R;  Learning Statistics using R; and Using R with Multivariate Statistics, Statistics Made Easy and Multivariate Statistics.  

Randall has published in several journals including Academic Medicine, Educational and Psychological Measurement, Journal of Applied Measurement, Journal of Educational and Behavioral Statistics, Journal of Research Methodology, Multiple Linear Regression, Structural Equation Modeling and Measurement:  Interdisciplinary Research and Perspectives. He has served on the editorial boards of numerous journals and is a member of the American Educational Research Association, Past-President of the Southwest Educational Research Association, and Emeritus Editor of the Structural Equation Modeling journal and Measurement:  Interdisciplinary Research and Perspective journal. 

Dr. Schumacker was the 1996 recipient of the Outstanding Scholar Award, and the 1998 recipient of the Charn Oswachoke International Award.  In 2010, he launched the DecisionKit App for the iPhone and iPad.  In 2011, he received the Apple iPad Award, and in 2012, he received the CIT Faculty Technology Award.  In 2013, he received the McCrory Faculty Excellence in Research Award from the College of Education at the University of Alabama.  In 2014, Dr. Schumacker was the recipient of the Structural Equation Modeling Service Award at the American Educational Research Association, where he founded the Structural Equation Modeling Special Interest Group.