STEVEN ANDREW CULPEPPER, PH.D.

Assistant Professor

Department of Mathematical and Statistical Sciences

University of Colorado Denver


 

My research focuses on statistical methods in the social sciences, in addition to research on substantive issues related to education and policy.  My statistical research currently centers on developing and assessing methods used in selection situations (e.g., admissions or pre-employment decisions).  I also conduct quantitative research on profile analysis methods and measurement error models.  I also enjoy participating in substantive research projects in the areas of education and the economics of education.  Additionally, I serve as a member of the National Indian Education Study Technical Review Panel, which is sponsored by the U.S. Department of Education through the National Assessment of Education Progress (NAEP).

Peer Reviewed Articles:

Culpepper, S. A. & Aguinis, H. (In Press). R is for revolution: A review of a cutting-edge, free, open source statistical package. Organizational Research Methods.

 

Culpepper, S. A. (In Press). Studying individual differences in predictability with gamma regression and nonlinear multilevel models. Multivariate Behavioral Research.

 

Culpepper, S. A. (2009). A multilevel approach for nonlinear profile analysis of dichotomous data. Multivariate Behavioral Research, 44, 646-667.

 

Aguinis, H., Pierce, C., & Culpepper, S. A. (2009). Scale coarseness as a methodological artifact: Correcting correlation coefficients attenuated from using coarse scales. Organizational Research Methods, 12, 623-652.

 

Culpepper, S. A. & Davenport, E. C. (2009). Assessing differential prediction of college grades by race/ethnicity with a multilevel model. Journal of Educational Measurement, 46, 220-242.

 

Culpepper, S. A. & Davenport, E. C., Jr. (2009). Identifying common high school coursework profiles with multidimensional scaling. IR Applications, 20, 1-18.

 

Culpepper, S. A., Davenport, E. C., Jr., & Davison, M. L. (2008). A method for choosing weights to predict college grades for admission decisions and to assess their fairness by race/ethnicity. Multiple Linear Regression Viewpoints, 34(2), 4-14.

 

Culpepper, S. A. (2008). Conducting external profile analysis with multiple regression. Practical Assessment, Research & Evaluation, 13(1).

 

Rapp, D. N, Culpepper, S. A., Kirkby, K., & Morin, P. (2007). Fostering students’ comprehension of topographic maps. Journal of Geoscience Education, 55(1), 5-16.

For additional information, please see my curriculum vitae.

 

Courses:

·        Math 1010: Mathematics for the Liberal Arts

·        Math 2830: Introductory Statistics

·        Math 4387/5387: Regression Analysis, Modeling and Time Series

·        Math 4830/5830: Applied Statistics

·        Math 5004: RM-MSMSP: Statistics and Probability

·        Math 6376: Statistical computing