Measurement, Evaluation, and Statistics | Teachers College Columbia University

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Academic Catalog 2017-2018

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Measurement, Evaluation, and Statistics

Department of - Human Development

Contact Information

(212) 678 4150
(212) 678 3837
Matthew Johnson (Applied Statistics) Young-Sun Lee (Measurement and Eval)

Program Description

The Measurement, Evaluation and Statistics area of study includes the following programs: Applied Statistics; and Measurement and Evaluation.

The M.S. in Applied Statistics (32 points) requires at three semesters of full-time study, and students can complete the program in 3 semesters (fall/spring/summer).  This master's degree provides training for a number of positions in applied research settings, testing organizations, and business organizations. In addition to the satisfactory completion of coursework, an integrative project is required. 

The Ed.M. in Measurement and Evaluation (60 points) is a two-year master's degree. It provides training for a number of positions in educational research bureaus and testing organizations. In addition to the satisfactory completion of coursework, an integrative project is required for the master's degree.

The Ed.D. and Ph.D. programs in Measurement and Evaluation are designed to prepare graduates for careers in a wide range of educational settings. Graduates acquire specialized knowledge and skills in test theory, test and instrument development and validation, program evaluation, and quantitative analysis of educational and psychological data. Some graduates pursue careers as college professors. Some are employed in city or state departments of education in the planning and supervision of testing programs and research and evaluation projects. Others work for test publishers, licensure and certification boards, and government agencies in the construction of tests or in the management of large-scale testing programs. Still others work in evaluation, research design, and statistics in contrast research firms, as well as health care and business settings. 

A doctorate is required for most college teaching positions and for positions of professional responsibility in testing organizations, departments of education, and licensure and certification boards. The Ph.D. (75 points) is appropriate for individuals with strong quantitative and technical skills who wish to focus on theoretical issues in measurement and evaluation or who have a strong background in a substantive area of psychology in which they wish to further the development and application of measurement techniques.

The Ed.D. (90 points) is appropriate for individuals who wish to focus on the application of measurement and evaluation techniques in education, psychology, and business and industry. Both doctoral degrees are accepted as qualification for faculty positions in schools of education in the United States.

Degree Summary

APPLIED STATISTICS (STAT)

  • Master of Science (M.S.)

MEASUREMENT AND EVALUATION (MEAS)

  • Master of Education (Ed.M.)
  • Doctor of Education (Ed.D.)
  • Doctor of Philosophy (Ph.D.)

For a complete listing of degree requirements, please click the "Degrees" tab above

For a complete listing of degree requirements, please continue on to this program's "Degrees" section in this document

Degree Requirements

Master of Science - 32 points

Applied Statistics Core Courses (18 points):
The following courses are required (in special circumstances, substitute courses may be approved by an advisor.): 

  • HUDM 4125 Statistical inference (3)
  • HUDM 5126 Linear models and regression analysis (3)*
  • HUDM 6026 Computational statistics (3)
  • HUDM 5150 Statistical Careers, Communications and Capstone (3)
    and at least one of:
  • HUDM 5123 Linear models and experimental design (3)
  • HUDM 6030 Multilevel and longitudinal data analysis (3)
    and at least one of:
  • HUDM 6055 Latent structure analysis (3)
  • HUDM 6122 Multivariate analysis (3)

*Under special circumstances HUDM 5122 may be substituted for HUDM 5126; advisor approval is required. 

Statistics Electives (9 points):

Other advanced statistics courses offered by the program or by other departments/schools of Columbia University may be selected, in consultation with an advisor, to complete the 18-point requirement. Examples of candidate courses include: HUDM 5059, HUDM 5124, HUDM 5130, and HUDM 5133. 

Breadth Requirement (6 points):
At least 6 points must be taken at Teachers College from outside the program in Measurement, Evaluation, and Applied Statistics. Note: A Mathematics Education course satisfies one of the two required breadth courses. 

Culminating Experience: 
A special project that is conducted in consultation with an advisor. Please contact Chanel Harry (ch3196@tc.columbia.edu) for more information.

Transfer Credit:
For the M.S. degree, no transfer credit is granted for work completed at other universities. 


Master of Education - 60 points

Measurement and Evaluation Core Courses (12 points):

  • HUDM 5059 Psychological measurement (3)
  • HUDM 6051-6052 Psychometric theory I and II (3 each)
  • HUDM 6055 Latent structure analysis (3)

 And at least 6 points selected from the following:

  • T6416 Program evaluation in social services (3) at School of Social Work
  • P8582 Program evaluation design for health policy and management (3) at Mailman School of Public Health
  • P8640 Methods in program evaluation (3) at Mailman School of Public Health
  • P8705 Evaluation of health programs (3) at Mailman School of Public Health

Quantitative Methods (15 points):

  • HUDM 4122 Probability and statistical inference (3)*
  • HUDM 5122 Applied regression analysis (3)*
  • HUDM 5123 Linear models and experimental design (3)
  • HUDM 6030 Multilevel and longitudinal data analysis (3)
  • HUDM 6122 Multivariate analysis (3)

*HUDM 4125 may be substituted for HUDM 4122 and HUDM 5126 may be substituted for HUDM 5122. 

Psychology (12 points):
Courses are taken in one or more of the following areas: developmental psychology, cognitive studies, counseling psychology, organizational psychology, or social psychology.

Research Methods (6 points):

  • HUD 4120 Methods of empirical research (3)
  • HUDM 5250 Research practicum in measurement and evaluation (0-4)

Other Aspects in Education (6 - 9 points):
One course in foundations of education and two courses in curriculum and teaching and/or educational leadership, chosen in consultation with an advisor. 

Electives:
Chosen in consultation with an advisor and designed to strengthen and broaden the student’s professional preparation.

Culminating Experience:
A project that is conducted in consultation with an advisor. 

Transfer Credit:
For the Ed.M. degree, a maximum of 30 points of graduate credit may be transferred from other institutions. Only completed graduate courses with earned grades of B or higher will be considered for transfer credit. For more information, please speak with the Transfer Credit Coordinator in the Office of the Registrar. 

Satisfactory Progress:
Students are expected to make satisfactory progress towards the completion of degree requirements. If satisfactory progress is not maintained, a student may be dismissed from the program. Where there are concerns about satisfactory progress, students will be informed by the program faculty. 


Doctor of Education - 90 points

 

Measurement Core (15 points):

  •       HUDM 5059               Psychological measurement (3)
  •       HUDM 5124               Multidimensional scaling and clustering (3)
  •       HUDM 6051               Psychometric theory I (3)
  •       HUDM 6052               Psychometric theory II (3)
  •       HUDM 6055               Latent structure analysis (3)

Evaluation Core (12 points):

  •  HUDM 5130               Meta-analysis (3)              
  •  HUDM 5133               Causal inference for program evaluation (3)
  •  ORLJ 5040                 Research methods in social psychology (3)

 

 with at least one Evaluation course selected from the following:

  •        P8640                          Methods in program evaluation (3) (at Mailman School of Public Health)
  •        P8705                          Evaluation of health programs (3) (at Mailman School of Public Health)

 

     Quantitative Methods Core (18 points):

  • HUDM 4122*             Probability and statistical inference (3)
  • HUDM 5122*             Applied regression analysis (3)
  • HUDM 5123               Linear models and experimental design (3)
  • HUDM 6026               Computational statistics (3)
  • HUDM 6030               Multilevel and longitudinal data analysis (3)       
  • HUDM 6122               Multivariate analysis I (3)

  

*HUDM 4125 may be substituted for HUDM 4122 and HUDM 5126 may be substituted for HUDM 5122. 

Measurement, Evaluation, and Statistics Electives (18 points):

      In consultation with an advisor, students can choose 18 points of courses from the below list, as well as from advanced courses offered at Columbia University Statistics Department, Mailman School of Public Health, and programs across Teachers College. The following are suggested but not required:

     

      HUDM 5058               Choice and decision making (3)  

      P8120                          Analysis of categorical data (3) (at Mailman School of Public Health)

      P8121                          Generalized linear models (3) (at Mailman School of Public Health)

      W4640                        Bayesian statistics (3) (at the Columbia Statistics Program)

      HUDM 5250               Research practicum in measurement and evaluation (0-4)           

     

Psychology (18 points):

      In consultation with an advisor, a group of courses aimed at substantive preparation in the field of psychology.

 

Related Courses (6 points):

      Selected from the areas of curriculum development, guidance, applied human development, supervision, and administration, and in consultation with an advisor.

 

Dissertation Advisement and Seminar (minimum of 3 points):

HUDM 7500*                   Dissertation seminar (3 credits total, one semester)

required) 

HUDM 8900                     Dissertation advisement (0)

 

Special Requirements:

      The first two years require full-time study. In addition to the above coursework, an approved certification paper, successful performance on the certification examination, and completion of an approved doctoral dissertation are also required.

 

Transfer Credit

 

Of a planned program of 90 points, at least 45 points must be taken through Teachers College registration. A maximum of 45 points may be transferred from another university for the Ed.D. degree. Only completed graduate courses with earned grades of B or higher that appear on the student’s transcript from a regionally accredited institution may be considered for transfer credit. 

 

The student files a “Request for an Allocation of Graduate Credit” with the Office of the Registrar. Once the Registrar's Office determines the eligibility of courses for transfer, final determination of transfer credit is awarded at the discretion of the faculty advisor after evaluation of the courses for content and relevance to program requirements. The Office of the Registrar notifies the student of the results.

 

 

Satisfactory Progress

 

Students are expected to make satisfactory progress toward the completion of degree requirements. Program faculty annually review each student’s progress. Where there are concerns about satisfactory progress, students will be informed by the program faculty. If a student is performing below expectations, remedial work within an appropriate timeline may be required. If satisfactory progress is not maintained, a student may be dismissed from the program.

 

 


Doctor of Philosophy - 75 points

Measurement Core (15 points):

  •  HUDM 5059                     Psychological measurement (3)
  •  HUDM 5124                     Multidimensional scaling and clustering (3)
  •  HUDM 6051                     Psychometric theory I (3)
  •  HUDM 6052                     Psychometric theory II (3)
  •  HUDM 6055                     Latent structure analysis (3) 

 Evaluation Core (9 points):

  • HUDM 5130                     Meta-analysis (3)                    
  • HUDM 5133                     Causal inference for program evaluation (3)
  • ORLJ 5040                       Research methods in social psychology (3)

Quantitative Methods Core (21 points):

  • MSTM 5030                      Topics in probability theory (3)
  • HUDM 4125                     Statistical inference (3)
  • HUDM 5123                     Linear models and experimental design (3)
  • HUDM 5126                     Linear models and regression analysis (3)
  • HUDM 6026                     Computational Statistics (3)
  • HUDM 6030                     Multilevel and longitudinal data analysis (3)
  • HUDM 6122                     Multivariate analysis I (3)

Measurement, Evaluation, and Statistics Electives (18 points):

In consultation with an advisor, students can select courses from the following list, as well as more generally from courses offered at other departments and schools at Columbia University:

  • HUDM 5058                     Choice and decision making (3)
  • P8120                                Analysis of categorical data (3) (at Mailman School of Public Health)
  • P8121                                Generalized linear models (3) (at Mailman School of Public Health)
  • W4640                              Bayesian statistics (3) (at the Columbia Statistics Program)
  • HUDM 5250                     Research practicum in measurement and evaluation (0-4)

 

Psychology (minimum of 9 points):

In consultation with an advisor, a group of courses aimed at substantive preparation in the field of psychology.

Dissertation Advisement and Seminar (minimum of 3 points):

HUDM 7500*                   Dissertation seminar (total 3 points, one semester)

required) 

HUDM 8900                     Dissertation advisement (0)

 

Special Requirements:
The first two years require full-time study. In addition to the above coursework, an approved empirical paper, an approved research paper, successful performance on the certification examination, and completion of an approved doctoral dissertation are required for the Ph.D.

  

M.Phil. Degree

 The M.Phil. is an en passant degree awarded to those nearing the completion of the Ph.D. degree.  Students contact the Office of Doctoral Studies to file for award of the degree. 

To receive the M.Phil., the student must satisfactorily complete the following requirements:

1). Register for courses through Teachers College and maintain continuous registration.

2). File in the Office of Doctoral Studies an approved Program Plan of Study, including transfer credit.

3). Complete not less than six courses with evaluative grades, under Teachers College registration, with a minimum composite grade decile of 6.

4). Pass the departmental Certification Examination (i.e., Research Methods Examination).

5). Complete an approved empirical research paper and an approved theoretical research paper.

6). Satisfactorily complete a minimum of 75 points of graduate credit, as indicated on the Program Plan (some programs exceed this minimum), and all program requirements for the Master of Philosophy degree.

7). Be recommended by the program advisor and department chair for the award of the M.Phil. degree, which signifies certification as a Ph.D. degree candidate who may continue the dissertation requirement under the auspices of the Teachers College faculty.

Candidates should provide copies of the program plan and both research papers to the Department of Human Development for inclusion in the student’s records.

 Transfer Credit

 Relevant courses completed in other recognized graduate schools to a maximum of 30 points, or 45 points if completed in another Faculty of Columbia University, may be accepted toward the minimum point requirement for the degree.

 Only completed graduate courses with earned grades of B or higher that appear on the student’s transcript from a regionally accredited institution may be considered for transfer credit. 

 The student files a “Request for an Allocation of Graduate Credit” with the Office of the Registrar.  Once the Registrar's Office determines the eligibility of courses for transfer, final determination of transfer credit is awarded at the discretion of the faculty advisor after evaluation of the courses for content and relevance to program requirements.  The Office of the Registrar notifies the student of the results.

 

 Satisfactory Progress

 Students are expected to make satisfactory progress toward the completion of degree requirements.   Program faculty annually review each student’s progress.  Where there are concerns about satisfactory progress, students will be informed by the program faculty.  If a student is performing below expectations, remedial work within an appropriate timeline may be required. If satisfactory progress is not maintained, a student may be dismissed from the program

 


Application Information

Applied Statistics 

GRE General Test is required for the M.S. in Applied Statistics. Background in calculus is also required. Current doctoral students in other disciplines at Teachers College can also apply; if interested contact the program director. 
 

Measurement and Evaluation 

GRE General Test is required for all programs in Measurement and Evaluation. For the Ph.D program, a background in calculus is also required. for the Ed.D, some preparation in college-level math or statistics is encouraged. 

Faculty List

Faculty

Lecturers

Visiting Faculty

Adjunct

Full-Time Instructors

Instructors

Professor of Statistics and Education
Professor of Psychology and Education
Associate Professor of Statistics and Education
Assistant Professor of Applied Statistics
Associate Professor of Psychology and Education
Associate Professor of Applied Statistics

For up to date information about course offerings including faculty information, please visit the online course schedule.

Course List

HUD 4120 Methods of empirical research
An introduction to the methods of scientific inquiry, research planning, and techniques of making observations and analyzing and presenting data.
HUDM 4050 Introduction to measurement
An introduction to basic concepts and issues in measurement. Descriptive statistics, scales of measurement, norms, reliability, validity. Advantages and limitations of measurement techniques are discussed and illustrated.
HUDM 4120 Basic concepts in statistics

Descriptive statistics including organizing, summarizing, reporting, and interpreting data. Understanding relationships expressed by cross-tabulation, breakdown, and scatterdiagrams. Designed as a one-semester introduction to statistical methods. Will include reading journal articles.

HUDM 4122 Probability and statistical inference

Elementary probability theory; random variables and probability distributions; sampling distributions; estimation theory and hypothesis testing using binomial, normal, T, chi square, and F distributions.

HUDM 4125 Statistical inference

Prerequisite: Course in Calculus. Calculus-based introduction to mathematical statistics.  Topics include an introduction to calculus-based probability; continuous and discrete distributions; point estimation; method of moments and maximum likelihood estimation; properties of estimators including bias and mean squared error; large sample properties of estimators; hypothesis testing including the likelihood ratio test; and interval estimation.

HUDM 4901 Research and independent study: Measurement and evaluation
Permission required.
HUDM 4902 Research and independent study: Applied statistics
Permission required.
HUDM 5000 HUDM Statistics Lab

Students in this lab must also be enrolled in HUDM 5122 or HUDM 5123.

HUDM 5026 Intro to Data Analysis in R

This course provides an introduction to the R language and environment for statistical computing with an emphasis on the application of fundamental graphical and statistical techniques. While some theory will be presented (for example, when discussing regression models), the focus will be on implementation and interpretation as opposed to study of the statistical properties of the methods.

Prerequisite: HUDM 4122. A course in regression is also recommended.
HUDM 5058 Choice and decision making

Prerequisite: HUDM 4122 or equivalent. Surveys quantitative models of individual decision making, from the introduction of the notion of "utility" by Daniel Bernoulli through current models such as Tversky and Kahneman's "Prospect Theory." The focus is on psychological or descriptive models of how people make decisions, although methods of rational decision analysis are briefly discussed.

HUDM 5059 Psychological measurement

A previous course in statistics or measurement is recommended. An in-depth examination of measurement and associated techniques, norms, classical test theory, reliability, validity, item response theory, issues, and applications. Open to doctoral students and Ed.M students in psychology; others only by permission.

HUDM 5122 Applied regression analysis

Least squares estimation theory. Traditional simple and multiple regression models and polynomial regression models, with grouping variables including one-way ANOVA, two-way ANOVA, and analysis of covariance. Lab devoted to applications of SPSS regression program.

HUDM 5123 Linear models and experimental design

Analysis of variance models including single and multiple factor experiments, between-subject and within-subject designs, trend analysis, factorial and nested designs, random effects, analysis of covariance, and blocking. Lab devoted to computer applications.

HUDM 5124 Multidimensional scaling and clustering
Permission required. Prerequisites: HUDM 4122 and HUDM 5122 or equivalent. Methods of analyzing proximity data (similarities, correlations, etc.), including multidimensional scaling, which represents similarities among items by plotting the items into a geometric space, and cluster analysis for grouping items.
HUDM 5126 Linear models and regression analysis

Introduction to the theory and application of linear regression using calculus and matrix algebra.  Focus on multiple regression models including dummy variables and polynomial models, regression diagnostics, and advanced methods such as weighted least squares, multilevel models, and an introduction to the generalized linear model.

HUDM 5150 HUDM Statistical Careers, Communication, and Capstone

This is a capstone course to the M.S. in Applied Statistics degree. In it students will discuss best practices in statistical analyses, including the role of a consultant and ethical issues encountered in analyses. Students will also study best practices for effective communication of statistics, including verbal, written, and graphical. Students will produce a capstone paper integrating the methods and skills they have learned across the M.S. degree.

Prerequsite: Students must have completed at least 24 points of the M.S. in Applied Statistics degree.

HUDM 5250 Research practicum in measurement and evaluation
Permission required. Students enrolled are expected to spend a semester involved in a research project, either assisting a faculty member or in an applied setting. A formal report will be submitted.
HUDM 6026 Computational statistics

Prerequisite: HUDM 4125 and either HUDM 5122 or HUDM 5126. Provides an introduction to computationally intense methods in applied statistics, taught in R. Topics include methods of evaluating statistical estimators; design, implementation, and reporting of Monte Carlo simulation studies; resampling and reordering methods; and nonparametric and data mining approaches to regression.

HUDM 6030 Multilevel longitudinal data analysis
Prerequisite: HUDM 5122. Multilevel models include a broad range of models called by various names, such as random effects models, multi-level models, and growth curve models. This course introduces the background and computer skills needed to understand and utilize these models.
HUDM 6051 Psychometric Theory I

Permission required. Prerequisites: HUDM 5059, HUDM 5122, or equivalents. Classical test theory and applications and test/instrument development and validation. 

HUDM 6052 Psychometric theory II

Permission required. Prerequisites: HUDM 6052 or equivalent. Item response theory and applications and cognitive diagnostic models.

HUDM 6055 Latent structure analysis
Permission required. Prerequisite: HUDM 5122. Recommended: HUDM 6122. Study of latent structure analysis, including measurement models for latent traits and latent classes, path analysis, factor analysis, structural equations, and categorical data analysis.
HUDM 6122 Multivariate analysis I

Prerequisite: HUDM 5122 or HUDM 5126; HUDM 5123 is recommended. An introduction to multivariate statistical analysis, including matrix algebra, general linear hypothesis and application, profile analysis, principal components analysis, discriminant analysis, and classification methods.

HUDM 6900 Advanced research and independent study
Permission required.
HUDM 7500 Dissertation seminar

Permission required. Development of doctoral dissertations and presentation of plans for approval. Registration limited to two terms. Ph.D & Ed.D students must complete 3 points over 2 semesters prior to proposing their dissertation. 

HUDM 8900 Dissertation advisement

Individual advisement on doctoral dissertation. Fee to equal 3 points at current tuition rate for each term. See section in catalog on Continuous Registration for Ed.D./ Ph.D. degrees. Ed.D & Ph.D students must register for this every semester while completing their dissertation.