Syllabus Education 795 Quantitative Methods for Non–Experimental Research




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Syllabus
Education 795
Quantitative Methods for Non–Experimental Research
University of Michigan School of Education, Winter 2004

Instructors: Eric Dey Heidi Grunwald

1110 SEB 2102 SEB

dey@umich.edu heidig@umich.edu




Office hours: By appointment Tuesdays 10-12p or


Email dey@umich.edu to schedule by appointment 615-3349

Schedule Lecture: Wed, 1-4pm, 2224 SEB


Computing lab: Thu, 5-7pm, Angell Hall Computing Site Classroom D
Home page: http://www.umich.edu/~ed795/
Email list: ed795.class@umich.edu
Overview

Education 795 is a second course in how to do quantitative research in the field of education. Upon completion of this course you will be able to use SPSS statistical software and appropriate statistical reasoning to make sense out of a body of quantitative data. Our primary focus will be on developing a conceptual understanding of quantitative research methods and the practical application of these methods in educational and other non–experimental settings. An emphasis will also be placed on developing skills needed to understand published research and present original research findings to professional audiences.

The course is organized into three main sections:
I. Review and extension of the basic statistical concepts and methods introduced in introductory educational statistics courses.
II. Research design and analysis issues, and introduction to factor analysis, scale construction, and advanced predictive techniques.
III. Extension and application of the topics previously introduced, with an emphasis placed on multiple regression, factor analysis and path analysis.
Like most social science research, educational research is typically a group activity. As such, group work will be emphasized throughout the course. In addition, students are encouraged to communicate, ask questions, and engage in electronic discussions via electronic mail. A basic class email address has been established which will automatically distribute questions and comments to all those affiliated with the course (send email to ed795.class@umich.edu).

Activities, Assessment, and Evaluation Details

Weekly research and writing assignments are the core of this course. By completing these assignments through your work in the lab session, you will develop and demonstrate the knowledge and skills needed to undertake quantitative data analysis. Keeping up to date with these is crucial: You must understand the previous material in order to follow what comes next. It is imperative that you do each set of exercises completely and on time. Exercises are due at the beginning of class the week after they are assigned; they will be read and returned the following week. Late assignments will be accepted, but they will be graded down substantially (25 percent reduction for any late submission; 50 percent reduction for those assignments more than one week late).

In addition to the weekly assignments, there will be a major peer–reviewed research report due at the end of the course. This report will be of the scope, scale, and quality of those presented at professional conferences and published in academic journals. This assignment is intended to be done individually, though in cases of overlapping interests a few students working together will be an option. On March 10th you will be asked to turn in a short description of the final project that you plan to undertake, and the data base you intend to use for your study. This should include a general description of the research questions you plan to investigate, the subset of cases you plan to use in your analyses and the main variables to be considered.

The first group of the weekly assignments will be relatively structured and based upon one of several data sets that will be provided to you. After this start-up period, assignments will become increasingly unstructured so that you can use lab time to work on the major research report due at the end of the term. Once we make this shift you are encouraged to use other data sets in your laboratory work as this will facilitate the final project report described above. In addition to this original research, a few of the weekly assignments will be used to provide a forum within which we can review published research.


For the purpose of assigning grades, student performance will be evaluated as follows:
1. Weekly assignments — 40% of course grade
Almost every week in this course there will be due a short (3 to 5 pages) research and writing assignment. As described above, these exercises will be due in class the week after they are assigned; they will be read and returned the following week. Handwritten exercises will not be accepted and late assignments will be graded down substantially. Of the weekly assignments, we will drop the one with the lowest score in computing the final grade if all assignments have been turned in during the semester. This is to encourage you to complete all assignments. If one or more assignments are missing, we will calculate this component of the final grade by assigning a grade of zero to each missing assignment before averaging the scores on all assignments.

2. Peer–reviewed Research Report — 40% of course grade


In addition to the weekly writing assignments, there will be a somewhat larger research project (approximately 15 - 20 pages) that will be peer reviewed by other members of the class. This larger project will require the analysis of data to answer a substantive research question. The scope and format of this project will be that of conference presentations or short research articles that appear in scholarly journals. The format of the final written products should conform to the standards in the American Psychological Association publication manual.
3. Review of Research Report — 10% of course grade
In addition to writing a Research Report, each student will review a Research Report written by another member of the class and provide suggestions for improvement. These reviews will be submitted to the instructor by the author of the review; authors of the Research Report will be asked to revise their Report in light of the suggestions of the reviewer. These reviews will count toward the reviewer’s grade, but will not have any impact on the grade of the group which wrote the report being reviewed.
4. Quality of participation — 10% of course grade
Since it is important to keep up-to-date with all assignments, attendance is strongly encouraged in the class and in the lab. Even if you are tempted to skip a class or lab session because you think you can complete the assignment on your own, you can still contribute to class by helping others learn the material and complete the assignments. Therefore, 10% of the course points will be given for attendance and quality of participation.

Readings
All readings need to be completed before class on the assigned date, and should be brought to class for reference.
Required texts:

Pedhazur, E.J. & Pedhazur-Schmelkin, L. (1991). Measurement, Design, and Analysis: An An Integrated Approach Hillsdale, N.Y: Lawrence Erlbaum Associates.

Aldrich, J.H. & Nelson, F.D. (1984). Linear Probability, Logit, and Probit Models. Newbury Park: Sage Publications


Tentative course schedule



Date



Topics


Reading assignment

Jan. 7


Presentation1

Course Overview and Procedures


Basic Review of Simple Linear Regression

No Reading Assignment


Jan. 14


Presentation2

The Role of Theory

Review Regression

Further Review



Ped, Ch 9 p 180-187

Skim Ped, Ch 17 p 366-388,

Read Ch 18 p 413-420


Jan. 21


Presentation3

The Literature Review and

Regression Diagnostics

Ped, Ch 9 p 191-194

Ped Ch 17 p 389-411

Jan. 28


Presentation4

P-Values and Decision Based Strategy

Partial Correlation, Multi-Collinearity

Ped, Ch 9 p 200-210

Ped, Ch 18 p 421-441, p448-451

Feb. 4


Presentation5

Nonexperimental Designs

Categorical Independent Variables Statistical Control

ANCOVA, Interactions, Statistical Control, Adjusted Means



Ped, Ch 14 p304-310

Ped, Ch 19 p 464-466

Ped Ch 10 p 211-216

Ped, Ch 21 p 545 – 558, p 567 - 579

Feb. 11


Presentation6

Rating Scales, Factor Analysis

Factor Analysis

Ped Ch 3 p 32-39, Ch 4 p 66-70

Ped Ch 22 p 590 – 606

Feb. 18


Presentation7

Content Validity, Reliability


Factor Analysis Cont.,

Ped, Ch 4 p 79-80, Ch 5 p 81-83,

p 92-94, 109-110

Ped, Ch 22 p 607-627,




Feb. 25

Winter vacation

Detective novels

Mar. 3


Presentation8

Rating Scales

Affirmative Action Case Study

Ped, Ch 6 p119-131

Assigned Readings handed out in class


Mar. 10

Presentation9



Quasi-Experimental Designs

Intro to CFA

SEM, Path Analysis


Ped, Ch 13 p 277 - 281

Ch 23 p 631-632

Ped Ch 24 p 695 – 699, p 720- 723

Mar. 17


Presentation10

Applied Research

Logistic Regression

Ped, Ch 7 p152-157

Aldrich & Nelson, All (Read carefully p. 30-73)

Mar. 24


Presentation11

Logistic Regression Week 2



Read: The Status of Women and Minorities Among Community College Faculty. Perna. L.W. (2003) Research in Higher Education 44(2) p. 204-240



Mar. 31


Presentation12

Data Analyst Pitfalls,

Difference Scores

Effect Sizes


Ped Ch 11 p 247-249,

Ped Ch 13 291-295

Ped Ch 15, 336-339, Handout


Apr. 7


Review
Note: Papers to Peer-reviewers by April 9th. Reviews back to authors by April 13th.



REVIEW / CATCH UP


Apr. 14


Presentations – Expanded class, 1-5pm


Note: All course materials submitted for evaluation due by 4pm, Friday April 16th






January 2004 — Page


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