Keith
Markus' Urban Sprawl:
http://web.jjay.cuny.edu/~kmarkus
EPSY U73000 GC
Introduction to Psychometrics
CRN 59467
This course is equivalent to PSY U76000 Psychometric Methods
Syllabus
Spring 2019
Time: Wednesday 6:30-8:30
PM
Room: GSUC 3212
(365 Fifth Avenue)
Contact Information:
Professor Keith A. Markus
kmarkus@aol.com (This is
the best way to contact me.)
212-237-8784 (Email
will generally reach me before voice mail.)
Office: 10.65.04
(New Building, John Jay College)
Address: Psychology Department, 10th Floor
John Jay College of Criminal Justice, CUNY
524 W59th Street, New York, NY, 10019
Office Hours: Wednesdays 5:15 PM to 6:15 PM GC room
3204.02.
(It usually works best to email me first, I can answer most
questions by email. Please be aware that I do not have access
to Graduate Center voice mail.)
Course Description: The course offers a general
introduction to psychometric methods primarily emphasizing
classical test theory, test construction and validation, and test
use. The emphasis lies with developing a firm understanding
of basic psychometric concepts. This course lays a
foundation for more advanced courses in specific topics introduced
here. The course understands psychometrics and testing as applying
broadly, not just to paper and pencil tests but also to
performance assessments, behavioral observations, measured
variables in experiments and quasi-experiments, surveys, and other
forms of behavioral data collection. However, much of the material
will emphasize measurement involving multiple indicators of a
common construct.
Course Objectives: The
course assumes a foundation in basic statistics and a healthy
curiosity but little more. The more you put into the course, the
more you will get out of the course. The course design reflects
the following objectives.
1. Students will gain a basic understanding of the foundations of
test theory that will prepare them to pursue more advanced topics
(e.g., item response theory, structural equation modeling).
2. Students will gain the background and confidence to critically
read technical manuals and other documentation in conjunction with
use of published tests.
3. Students will gain facility with conceptual tools for thinking
through issues of validity and reliability as applied to all
measures from dependent variables in experiments to large scale
testing programs.
4. Students will gain a level of comfort with algebraic
representations of test scores and the use of these to think
through applied problems related to test use and interpretation.
5. Students will gain an increased sensitivity to the fallibility
of educational and psychological tests and the limits to their use
and interpretation.
6. Students will gain exposure to the use of statistical software
for conducting psychometric analyses and some experience with such
analyses.
Text Book:
Bandalos,
D. L. (2018). Measurement Theory and Applications for the Social
Sciences. New York: Guildford. The book will not
be available until January 31. I will provide draft chapters
as needed until the book is available. There are provided
for your personal use only and cannot be shared or distributed.
Additional
Reading:
American Educational Research Association, American Psychological
Association & National Council on Measurement in Education
(2014). Standards for educational and
psychological testing. Washington, DC: AERA.
Suggested Reading:
Markus, K. A. & Borsboom, D. (2013). A theory of test
score interpretation. (from Markus, K. A. & Borsboom, D.,
2013. Frontiers of test validity theory. New York:
Routledge.)
Course Flow: Familiarize yourself with the reading
material before the corresponding lecture. Lectures will
summarize and clarify the reading. In general, I would rather
answer your questions than lecture. I will use class time to
illustrate and amplify particularly tricky points based on past
experience. I will not focus on unimportant material in class, but
there will be some important material that I do not focus on in
class.
I will illustrate psychometric concepts primarily using
spreadsheets and R. Familiarity with the software is not a
course requirement. However, learning psychometrics simply by
reading about it is akin to learning to swim, ski, or play a
musical instrument simply by reading about it. Actual practice is
a much more effective method. Whether you use a simple calculator,
a spreadsheet, or advanced statistical software, it is a good
habit to play around with the material by constructing concrete
examples and taking a try-and-see attitude toward the material. If
something seems puzzling, make up an example and try it out. If
something seems counter-intuitive to you, try to construct a
counterexample. The more concrete you make psychometrics, the more
comfortable you will feel with the material, the better you will
understand it, and the more skills you will develop that you can
apply outside of the class. None of the this is required for the
course, but it will make it more fun, more interesting, and more
valuable at a practical level.
Course Project:
The course project is broken into four parts: topic, and Parts 1 to
3. Details of the assignment along with R scripts will be
provided through Blackboard. Due dates are listed below on the
course schedule.
Grading: The course project is the only graded
assignment. The topic is worth 10%, Part 1 25%, Part 2 30% and
Part 3 35%. Letter grades will be assigned as indicated
below.
Letter Grade
|
Percent Grade
|
A
|
92-100
|
A-
|
84-91
|
B+
|
76-83
|
B
|
68-75
|
B-
|
60-67
|
C+
|
52-59
|
C
|
44-51
|
C-
|
36-43
|
F
|
0-35
|
Special Needs:
To request accommodations please contact the Office of the Vice
President for Student Affairs (Room 7301 Graduate Center; (212)
817-7400). Information about accommodations can be found in the
Graduate Center Student Handbook 05-06, pp. 51-52).
Academic Honesty:
The Graduate Center of The City University of New York is committed
to the highest standards of academic honesty. Acts of academic
dishonesty include—but are not limited to—plagiarism, (in drafts,
outlines, and examinations, as well as final papers), cheating,
bribery, academic fraud, sabotage of research materials, the sale of
academic papers, and the falsification of records. An individual who
engages in these or related activities or who knowingly aids another
who engages in them is acting in an academically dishonest manner
and will be subject to disciplinary action in accordance with the
bylaws and procedures of The Graduate Center and the Board of
Trustees of The City University of New York.
Each member of the academic community is expected to give full,
fair, and formal credit to any and all sources that have contributed
to the formulation of ideas, methods, interpretations, and findings.
The absence of such formal credit is an affirmation representing
that the work is fully the writer’s. The term “sources” includes,
but is not limited to, published or unpublished materials, lectures
and lecture notes, computer programs, mathematical and other
symbolic formulations, course papers, examinations, theses,
dissertations, and comments offered in class or informal
discussions, and includes electronic media. The representation that
such work of another person is the writer’s own is plagiarism.
Care must be taken to document the source of any ideas or arguments.
If the actual words of a source are used, they must appear within
quotation marks. In cases that are unclear, the writer must take due
care to avoid plagiarism.
The source should be cited whenever:
(a) a text is quoted verbatim
(b) data gathered by another are presented in diagrams or tables
(c) the results of a study done by another are used
(d) the work or intellectual effort of another is paraphrased by the
writer
Because the intent to deceive is not a necessary
element in plagiarism, careful note taking and record keeping are
essential in order to avoid unintentional plagiarism.
For additional information, please consult
“Avoiding and Detecting Plagiarism,” available in the Office of the
Vice President for Student Affairs, the Provost’s Office, or at
http://web.gc.cuny.edu/provost/pdf/AvoidingPlagiarism.pdf.
(From The Graduate Center Student Handbook 05-06, pp. 36-37)
Schedule
Date
|
Topics
|
Reading Due
|
Assignments Due
|
Week 1 W 1/30
|
Course overview & Models of test scores
|
History of Testing |
|
Week 2 W 2/6
|
Scale development
|
The Scale Development Process & Standards Ch. 4 |
|
Week 3 W 2/13
|
Norms and standard scores
|
Norms & Standardized Scores & Standards Ch. 5 |
Post Choice of Project Topic
|
Week 4 W 2/20
|
Cognitive items
|
Types of Items -- Cognitive |
|
Week 5 W 2/27
|
Affective items
|
Types of Items -- Affective |
|
Week 6 W 3/6
|
Item analysis
|
Item Analysis & Standards Ch. 7 |
Project Part 1 |
Week 7 W 3/13
|
Reliability (part one)
|
Reliability 1: Reliability & Standards Ch 2 |
|
Week 8 W 3/20
|
Reliability (part two)
|
Reliability
2:
Ways of Assessing Reliability
|
|
Week 9 W 3/27
|
Validity (part one)
|
Validity (pp. 1-27) &
Standards Ch 1
|
|
Week 10 W 4/3
|
Validity (part two)
|
Validity (pp. 27-71)
|
|
Week 11 W 4/10
|
Factor Analysis
|
Exploratory Factor Analysis
|
Project Part 2
|
Week 12 W 4/17
|
Item Response Theory
|
Item Response Theory
|
|
Week 13 W 5/1
(No class 4/24)
|
Test equating
|
Test Equating (recall Standards Ch. 5) |
|
Week 14 W 5/8
|
Test bias & Test fairness
|
Test Bias and Legal Issues & Standards Ch. 3 |
|
Week 15 W 5/15
(no meeting)
|
Open office hours for project questions |
|
|
5/22 (no meeting)
|
(Last day of final exam week) |
|
Project Part 3 |
Created January 27, 2008
Updated January 24, 2019
This page was created using Mozilla
SeaMonkey v.2.49.1
and is best viewed using a Mozilla web browser.