Advanced Quantitative Methods Elective Options for Ph.D. Students in EDL

Questions to Consider for Advisors and Students

  1. Is it likely the student will utilize quantitative methods in their dissertation?
  2. How well did the student perform in EPE/EDP 660.  Did they like the class?
    1. Students who did not perform at their peak in EPE/EDP 660 or, after having taken the course feel they don’t have a passion for quantitative approaches, may not be interested in advanced topics in this area.
  3. What quantitative analyses are being employed by researchers who publish in EAQ, JEA, EEPA, AERJ, etc.? Knowing the answer to this can help students determine what approaches are likely to be:
    1. Accepted for publication in journals
    2. Palatable to peers during conference presentations or university job talks
  4. Does the student live outside Lexington and must take only courses designated as distance learning (DL)?
    1. Students who are paying in-state tuition as a result of being in a distance learning program can have all their tuition costs raised to out of state levels by enrolling in just one non-DL course.
  5. Is the student taking part in the UK Employee Education Program and must take a distance learning course.
    1. Students taking advantage of the UK Employee Education Program are not subjected to tuition charges and thus will not be impacted by taking a non-DL course.

Advanced Quantitative Elective Options


As of  October 12, 2017 may not be Distance Learning. Please check before registering.

This is a measurement-oriented course that focuses on introducing measurement theory and techniques used in education and evaluation. Topics to be covered include, but are not limited to, measurement models, bivariate measures of association, norms, standardized score scales, scaling, reliability, validity, item analysis, factor analysis, confirmatory factor analysis, test construction for affective and cognitive instruments, Item Response Theory, and Rasch. The course aims to familiarize students with measurement terminology, possess a detailed strategy for constructing an instrument suitable for research purposes, become familiar with statistical procedures and software for implementing measurement techniques, gain requisite foundation of knowledge necessary to learn more complex measurement models, and become more critical of measurement presentations in academic journals and the mass media. Prereq: EDP/EPE 660, EPE 621, or equivalent. (Same as EPE 679.)


As of  October 12, 2017 may not be Distance Learning. Please check before registering.

Multivariate statistics will prepare student to understand multivariate statistical methods and draw the link between statistics previously learned. Students will be able to conduct, interpret, and critique procedures such as factorial ANOVA, multiple regression, MANOVA, ANCOVA, MANCOVA, PCA, EFA, discriminant function analysis, logistic regression, canonical correlation, hierarchal linear regression, and multivariate analysis of change. Become familiar with statistical software for implementing multivariate procedures. Develop an understanding of the concepts, terms, and symbols used in multivariate statistics (e.g., Matrix Algebra, effect sizes). Gain an appreciation of the role of multivariate procedures in the research process. Gain the requisite knowledge necessary to learn more complex statistical procedures. Prereq: EDP/EPE 660 or equivalent. (Same as EDP 707.)


This course is intended to familiarize students with advanced quantitative techniques. Topics include structural equation modeling, item response theory, Rasch modeling, hierarchical linear modeling, and data mining. Other specific analysis techniques may also be explored. Prereq: Intermediate Statistics. (Same as EDP 711.)


This course will provide students with an overview of the theory and applications of advanced psychometric methods. A psychometric method focuses on advanced psychometric methodologies used in methodologically-oriented studies in educational measurement and evaluation techniques. The goal of this course is to prepare students to analyze data using advanced psychometric methods. It covers topics in the areas of Rasch Modeling, Item Response Theory, Structural Equation Modeling, Advanced Survey Techniques, and Latent Variable Modeling (as well as additional techniques). Given the advanced nature of the course, we will not shy away from using the mathematical tools needed to develop the conceptual understanding. But the emphasis of the course will be on the conceptual understanding and application of the tools rather than on the math or the mechanics behind the tools. Prereq: Intermediate Statistics. (Same as EPE 712.)