Latent Variable Modeling and Path Analysis- PubH 7435

Fall 2008, 3 credits

INSTRUCTOR: Melanie M. Wall, Division of Biostatistics, A426 Mayo Building, 625-2138 melanie@biostat.umn.edu
Office hours: 1:00-2:30, Wednesdays, Mayo A426

TIME AND PLACE: 9:45-11:00, T & Th, Location: Jackson Hall 2-137.

COURSE DESCRIPTION: Introduction to the use of statistical techniques known collectively as latent variable models, including exploratory and confirmatory factor analysis, path analysis, structural equation modeling, latent trait models and latent class models. SAS, AMOS and Mplus software will be used. The course is designed as an elective for biostatistics students yet any student (or post-doc or faculty) throughout the SPH and University with some background in statistics methods (equivalent of PubH 6450-6451) is welcome to attend.

NOTE: For PhD students in biostatistics or statistics who want to take this course to satisfy the division's PhD elective requirement, it should be signed up at the 8435 level and there will be a higher workload expected of the student. In particular, there will be more homework problems per assignment focused on statistical theory underlying the methods (which will usually involve an additional reading of a research paper), and higher expectations for the final project.

COURSE OBJECTIVES: To provide students: 1. the ability to recognize where these techniques may be useful, 2. the statistical theoretical background to understand how these models work, 3. the understanding of the limitations of these models, and 4. the ability to use current software for computation with these models.

PREREQUISITES: A one year course in applied statistics at the level of Pubh 6451 or Pubh 7406 or Stat 5303 or permission of the instructor.

METHOD OF INSTRUCTION AND WORK EXPECTATIONS: Classroom experience will be a combination of traditional lecture and hands-on computer lab experience (using SAS and the free student version of AMOS and Mplus) in the SPH Computer Lab or in class with laptops. Students may discuss homeworks and final projects with other class-mates but are expected to write-up homeworks and final project independently.

RECOMMENDED TEXTS:

• Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research by Marjorie A. Pett, Nancy R. Lackey, and John J. Sullivan, 2003, Sage Publishing
• Kline, R.B. (2005). Principles and Practice of Structural Equation Modeling, Second edition, Guilford.
• For the biostatistics and statistics graduate students taking the course, the additional following text is recommended...Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models by Anders Skrondal and Sophia Rabe-Hesketh, 2004, Chapman and Hall/CRC publishing

SOFTWARE:

• AMOS I have decided, due to its ease of learning, that I will be using the AMOS software in class. AMOS is now part of the SPSS software, so if you have SPSS you probably have AMOS. There is also a FREE stand alone student version of an older version of AMOS, AMOS 5, available for download from the web at www.amosdevelopment.com and clicking on Student version. There is also a nice guide Introduction to Structural Equation Modeling using AMOS created by some folks at UT-Austin which may be useful. HERE is a LONG list of citations that use AMOS.
• MPLUS I will be introducing this software which can handle categorical outcome variables, latent class modeling, and multilevel modeling. A FREE demo version of MPLUS 4.0 software is available for download from the web at www.statmodel.com/demo.html. Some very good resources (including full video lectures by Bengt Muthen) can be found at http://www.ats.ucla.edu/stat/mplus/
• Almost every analysis that can be accomplished in AMOS can also be performed with LISREL so if you are familiar with LISREL and prefer to use it there should be no problem, but I will give demonstrations with AMOS.
• SAS will also be used to perform some analyses

ASSESSMENT:

• Homework 50% (5 homeworks, approximately an assignment every other week)
  Homework is due in class (i.e. 9:45 a.m.). Sometimes Homeworks will involve questions that can be completed during computer lab time. Homework turned in after the time it is due will have 50% deducted. You may only turn in late homework up until the next homework is due, after that there will be no credit given.
• One in-class exam 25% (CHANGED DATE-->November 20th)
• Final Project 25% (written and oral presentation) The project will entail ONE of the following three options:
  • Option 1: A substantive description and detailed statistical analysis of some data set in which the analysis utilizes any of the latent variable modeling techniques learned in class.
  • Option 2: A detailed description and critique of a published paper in which a latent variable modeling technique was employed.
  • Option 3: Perform a simulation study or provide some analytical results for a statistical method for latent variable modeling.
  For all projects, a written report (6-8 pages not including graphs) outlining the problem, describing the analysis and summarizing the results will be required. The results will be presented to the class orally (15-minute presentation) during the last week of class and possibly during the finals period, 4:00-6:00 Wednesday Dec 17th. Grading of the project will be as follows: 2/3 of the project grade will come from the written report and 1/3 will come from your presentation. More Guidelines about the project. Also for a good guide to giving an effective presentation, check out http://www.enar.org/presentationguidelines.cfm
• GRADES will be assigned by combining Homework, Midterm and Final Project according to the percentages mentioned (i.e. Homework 50%, Midterm 25%, Final Project 25%).
  The grading scale based on the Total percentage is the following:
  • 93-100 A , 90-92 A-, 85-89 B+, 78-84 B, 75-77 B-, 70-74 C+, 65-69 C, 60-64 C-
  • For those taking the course S/N (Pass/Fail), an S will be earned if a grade equivalent to a C- or above is achieved.
  • For all students, if a grade of at least C- is not achieved, the grade will be F (or N).
  • The grading option (i.e. A/F or S/N) can ONLY be changed during the first two weeks of the semester. It CANNOT be changed after that.
  • An incomplete grade is permitted only in cases of extraordinary circumstances and following consultation with the instructor. In such cases an "I" grade will require a specific written agreement between the instructor and student specifying the time and manner in which the student will complete the course requirements. Extension for completion of the work will not exceed on year.
  • Withdrawal Policy
    • School of Public Health students may withdraw from a course through the second week of the semester without permission. No "W" will appear on the transcript.
    • After the second week students are required to do the following:
      1. The student must contact and notify their advisor and course instructor informing them of the decision to withdraw form the course.
      2. The student must send an e-mail to the SPH Student Services Center (SSC). The email must provide the student name, ID#, course number, section number, semester and year with instructions to withdraw the student form the course, and acknowledgment that the instructor and advisor have been contacted.
      3. The advisor and instructor must email the SSC acknowledging the student is canceling the course. All parties must be notified of the student's intent.
      4. The SSC will complete the process by withdrawing the student from the course after receiving all emails (student, advisor, and instructor). A "W" will be placed and remain on the student transcript for the course.
    • After discussion with their advisor and notification to the instructor, students may withdraw up until the eight week of the semester. There is no appeal process.

DISABILITY ACCOMMODATION It is University policy to provide, on a flexible and individualized basis, reasonable accommodations to students who have documented disability conditions (e.g., physical, learning, psychiatric, vision, hearing, or systemic) that may affect their ability to participate in course activities or to meet course requirements. Students with disabilities are encouraged to contact Disability Services for a confidential discussion of their individual needs for accommodations. Disability Services is located in Suite 180 McNamara Alumni Center, 200 Oak Street. Staff can be reached by calling 612/626-1333 voice or TTY. The website is http://ds.umn.edu

STUDENT CONDUCT, SCHOLASTIC DISHONESTY, AND SEXUAL HARASSMENT POLICY Students are responsible for knowing the University of Minnesota, Board of Regents' policy on Student Conduct and Sexual Harassment found at www.umn.edu/regents/polindex.html. Students are responsible for maintaining scholastic honesty in their work at all times. Students engaged in scholastic dishonesty will be penalized, and offenses will be reported to the Office of Student Academic Integrity (OSAI, www.osai.umn.edu). The University's Student Conduct Code defines scholastic dishonesty as "plagiarizing; cheating on assignments or examinations; engaging in unauthorized collaboration on academic work; taking, acquiring, or using test materials without faculty permission; submitting false or incomplete records of academic achievement; acting alone or in cooperation with another to falsify records or to obtain dishonestly grades, honors, awards, or professional endorsement; or altering, forging, or misusing a University academic record; or fabricating or falsifying of data, research procedures, or data analysis." Plagiarism is an important element of this policy. It is defined as the presentation of another's writing or ideas as your own. Serious, intentional plagiarism will result in a grade of "F" or "N" for the entire course. For more information on this policy and for a helpful discussion of preventing plagiarism, please consult University policies and procedures regarding academic integrity: http://writing.umn.edu/tww/plagiarism/ Students are urged to be careful that they properly attribute and cite others' work in their own writing. For guidelines for correctly citing sources, go to http://tutorial.lib.umn.edu/ and click on "Citing Sources". In addition, original work is expected in this course. It is unacceptable to hand in assignments for this course for which you receive credit in another course unless by prior agreement with the instructor. Building on a line of work begun in another course or leading to a thesis, dissertation, or final project is acceptable. If you have any questions, consult the instructor.

Division of Biostatistics
A460 Mayo Building MMC 303
420 Delaware Street S.E.
Minneapolis, MN 55455
(612)625-2138
melanie@biostat.umn.edu