1.	ERMA 8340
3 credit hours

2.	Semester SP 2013	
Instructor:	Margaret E. Ross
			4018 Haley Center
			(334) 844-3084	rossma1@mail.auburn.edu   (the first 1 = one)
Office Hours:	Tuesday 3:00 – 4:30 pm and Thursday 3:00 – 4:30 pm or by appointment
_____________________________________________________________________________________

3.	Resources

Required

Byrn, B. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Routledge
Tyler & Francis Group, LLC, NY.

Recommended

Arbuckle, J. L. (1995-2010). IBM SPSS(R) AMOSTM 19 User’s guide. http//www.amosdeveloment.com/amos.pdf
(or just search for AMOS 19 manual)

Mertler, Craig A. and Vannatta, Rachel A. (2010).  Advanced and Multivariate Statistical Methods: Practical
Application and Interpretation.  Pyrczak Publishing, Los Angelas.  

Publication manual of the American Psychological Association (6th ed.). Washington D.C.,
American Psychological Association.	

4.	Course Description
This course is designed to provide students the understanding of factor analytic statistical procedures.  Regression and path analysis, prerequisites for understanding factor analysis, are reviewed. This course emphasizes the conceptual and practical application of factor analysis.  Both confirmatory and exploratory procedures are addressed to provide an overall understanding of the various uses of factor analysis, including both measurement and structural models. A hands-on approach to analyzing data using AMOS and interpreting output is used.

5.	Course Objectives
Students will:
•	Gain an understanding of factor analytic procedures.
•	Apply knowledge of factor analysis by analyzing data to assess factor analytic models.
•	Apply knowledge of factor analysis through interpreting output and revising models as indicated by results
•	Interpret the results of the analyses in terms of the research hypothesis and/or purposes

6.	Tentative Course Content and Schedule

Class 1	Introduction and Syllabus
1/10/13	Large Scale Data Sets

Class 2	Matrix Algebra (Review)
1/17/13	ANOVA using Matrix Algebra
		Review and Extension of Regression Procedures
		Large Scale data Sets Specifying Variable Sets and Weighting 
		Download Data Set and Weighting Information

Class 3  	Path Analysis 
1/24/13	Path Coefficients
		Direct and Indirect Effects
		Path Analysis Assignment
		Send/upload Path Analysis Assignment
	
Class 4  	Exploratory Factor Analysis
1/31/13	Rotation
		Principal Axes, Principal Components
		Estimation procedures (Least Squares, ML, Bayes)
		Communalities
		Percent of Variance Explained
		Eigenvalues 
		Scree plot
		Structure and Pattern Coefficients
		Exploratory Factor Analysis (large scale data set)
		Send/Upload Annotated Exploratory FA Output and Model and Written Results Section
		(Annotation to be interpretation of major output components)
		Send/Upload Exploratory FA article summary

Class 5	Introduction to Structural Equation Modeling and AMOS
2/7/13	Model Specification Assignment
		Upload Specification Assignment
		Projects

Class 6	Identification 
2/14/13	Fit Indices
	Misspecification
	Non-centrality Parameter
	Confirmatory FA (large scale data set)
	Send/Upload Confirmatory FA Model and Annotated Output
		(Annotation to be interpretation of major output components)
		Send/Upload CFA Article list of statistics reported in results section and author’s interpretation
	Readings: Chapter 3

NO CLASS	EERA
2/21/13

Class 7   	Errors and Problems
2/28/13	Missing Data Solutions
	Non-Normality and bootstrapping
	Monte Carlo and Bootstrapping 
	Determinate of a Matrix
	Ill conditioned matrix
	Identifying Data Problems (large scale data set)
	Send/Upload Assessment of Data Problems
	Projects
	Readings: Chapter 12 and Chapter 13

Class 8 	The measurement model
3/7/13	Mahalanobis distance
	Non-centrality parameters
	Categorical varianble
	Bayesian estimates
	Postier probability
	Measurement Model (w second order factor) (large scale data set)
	Send/Upload Measurement Model and Annotated Output
		(Annotation to be interpretation of major output components)
		Projects
	Readings: Chapter 4 and Chapter 5

NO CLASS	Spring Bread
3/14/13

Class 9  	The Full Structural Model
3/21/13	Full Structural Model (large scale data set)
	Send/Upload Structural Model and Annotated Output
		(Annotation to be interpretation of major output components)	
		Send/Upload SEM (Full Structural Model) article summary
	Readings: Chapter 6

Class 10   	Multiple Group Equivalence
3/28/13	Multiple Group Equivalence (large scale data set)
	Send/Upload Multiple Group Model and Annotated Output
		(Annotation to be interpretation of major output components)
		Projects
	Readings: Chapter 7

Class 11  	Briefly Review Dummy Coding
4/4/13	Problems related to Post Hoc Model Fitting
	Multi-Trait Multi-Method Introduction
	Cross-validation
	Projects
	Readings: Chapters 8-10

Class 12  	Poster Presentations of In-class Projects
4/11/12
		
Class 13  	Latent Growth Modeling
4/18/13

Class 14	Roundtable and PowerPoint Presentations (for A – all welcome)
4/25/13			

7.	Course Requirements and Evaluation
Learning Methods
Lectures, discussions, readings, class exercises and lab assignments.

Student Assessment
In-class Assignments			
	Completion			25%
	Accuracy of interpretations	25%
In-class Projects				
	Completeness/Accuracy 		50%	
Authentic Projects			To be completed for an A
Roundtable Presentation			To be completed for an A (all welcome)

A – 	Completion of in-class assignments and project with at least 90% accuracy and completion of Authentic Project with at least 80% accuracy
B – 	Completion of in-class assignments and project with at least 80% accuracy	
C – 	Completion of in-class assignments and project with at least 70% accuracy	
D - 	Completion of in-class assignments and project with at least 60% accuracy	
F – 	Failure to meet minimum requirements for a D

•	You CANNOT make up more than 2 in-class assignments.  Thus, if you miss more than two assignments, your percent grade will be affected.

Authentic Project Outline

Introduction

Introduction to the research and statement of significance of the problem or issue addressed
Literature review (very short) 
Specific research questions to be answered. 
     	Are they clearly stated?
	Are they feasible/legitimate?
		Does it lend itself to t-test or ANOVA procedures?

Methodology

Participants
Full description of participants 

Measures
Instrumentation Description in detail (Validity and Reliability important here!)

Procedures
Procedures (detailed description of what you did – step by step)  
Data processing and analysis (how will you analyze the data and why)? 

Results

Are all appropriate statistics clearly stated in APA style?
Are tables or graphs appropriately used?

Discussion

Results in words
Results in light of past research/theory
Recommendations
Limitations discussed

A more detailed rubric will be handed out closer to the time the proposal and presentation are due.
The paper is to be written in APA style.

8.	Class Policy Statements

Attendance Policy
·	Excellent attendance is expected.
·	I will start class on time so if you are late you will need to get notes from another student.  
·	I will allow only two lab make-ups.  If you miss more classes you will not be able to earn the points for the assignment.

Late Assignments Policy  
•	Assignments turned in late will receive a 2% reduction in earned points per day.  The only exception will be in the case of emergency.
•	Except for work requiring calculations, all work must be typed or it will not be graded.  Late penalty will be applied to work completed in writing and then turned in late in typed format for a grade.

Incompletes and Withdrawals   
Grades associated with incomplete course work or withdrawal from class will be assigned in strict conformity to University policy (see Student Policy eHandbook, www.auburn.edu/studentpolicies).  If you wish to drop this course you may do so by the 10th class day with no grade assignment. From the 10th class day to mid-quarter a W (withdrawn-passing) grade will be recorded in your transcripts. After this period withdrawal from the course will only be granted under unusual circumstances and must be approved by the Dean of the College of Education.

Note that a new incomplete grade (IN) policy is in effect.  The new policy requires that students complete a form requesting that an IN grade be assigned.  If this form in not completed and given to the instructor of the class, a grade will be assigned with a score of zero (0) for work that has not been completed and turned in by the time the instructor reports grades.

Academic Misconduct 
The Department of EFLT recognizes university policy regarding academic misconduct. Violations include, but are not limited to: plagiarism, unauthorized assistance during examinations, submitting another’s work product as your own, using another’s words as your own without appropriate citation, sharing unauthorized materials with another that contain questions or answers to examinations, altering or attempting to alter assigned grades. In accordance with University policy regarding academic misconduct, students may be subject to several sanctions upon violations of the Student Academic Honesty Code. See the Student Policy eHandbook (www.auburn.edu/studentpolicies) for specifics regarding academic misconduct as well as student’s rights and responsibilities associated with the Code.

Disability Accommodations 
"Students who need accommodations are asked to electronically submit their approved accommodations through AU Access and to arrange a meeting during office hours the first week of classes, or as soon as possible if accommodations are needed immediately. If you have a conflict with my office hours, an alternate time can be arranged. To set up this meeting, please contact me by e-mail. If you have not established accommodations through the Office of Accessibility, but need accommodations, make an appointment with the Office of Accessibility, 1228 Haley Center, 844-2096 (V/TT)."