Sociology 523
Advanced Quantitative Research Methods
Spring 2008
Monday 2:00-4:50
Room: KAP 355
Professor
Merril Silverstein, Ph.D.
GERO 218B
740-1713
Office hours: by appointment
Required Texts
Luke, D. (2004) Multilevel Modeling. Newbury Park: Sage Publications.
Maruyama, G. (1998). Basics of Structural Equation Modeling. Newbury Park: Sage Publications.
McCutcheon, A. (1987). Latent Class Analysis. Newbury Park: Sage Publications.
Recommended for practical applications:
Byrne, B.M. (2001). Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming. Mahwah, NJ: Lawrence Erlbaum Associates.
Additional Readings
These can be found on a Docushare folder for Soc 523. On it, you will find readings in PDF, data sets in SPSS, and assignments in WORD. The URL is http://docushare.usc.edu.
The login information is:
username: soc523
password: merril
Then go to LDSàCoursesàGraduate
Course Description
This course will cover advanced methods in quantitative survey research, with an emphasis on structural equation, latent variable, and longitudinal modeling. The class will provide you with the research tools to write a publishable empirical article and is especially intended to provide practical training in the use of advanced methods and techniques that you may want to consider for your own empirical papers and/or dissertations.
While the statistical background of the procedures will be discussed, the emphasis will be on conceptual understanding and practical implementation of the techniques used, and the interpretation of results relative to the research questions posed. Several themes related to professional development will be on-going throughout the lectures of the course, including how to publish quantitative social science research, how to write an effective grant proposal, and how to make scientifically prudent decisions when doing survey research.
The course material assumes good working knowledge of multiple regression analysis; two basic statistics courses are considered a prerequisite for this course (or permission of the instructor).
We will be using SPSS-PC as a platform for all our analyses. Conversions from SAS and other export files can be accomplished using STAT-TRANSFER, which I can make available. Class-time will follow the following format: discussion of previous week’s exercise and readings, general overview of the current week’s topic, demonstration of procedure in computer lab as a guided exercise.
Course Requirements
1) There will be a computer lab session almost every week, with a demonstration that will take the form of a guided exercise. For each of these, you will write a short (1-2 page/double-spaced) summary of the exercise to be handed-in the following week. These reviews will be handed-in for credit, but not graded (8 class summaries @ 2 point each = 16 points).
2) For each class, applied background articles that use the covered technique will be assigned. You are required to make two in-class presentations and write two 4-5 page critiques the applied readings. These summaries/critiques will take 15-20 minutes, and should focus on the method used, its relation to the research problem, why it was appropriate, and the interpretation it allowed the researcher to make. Other issues may be brought up as appropriate. One or two students will be assigned each week. Note that student presentations will be made and the week after the topic is covered in class. (2 critiques/presentations @ 12 points each = 24 points).
3) A 3-4 page proposal for your final project will be due by February 25, and will be presented in class for discussion and comment. It is strongly suggested that you consult with me before starting your proposal, particularly if you need to find an appropriate data set.. The project should use quantitative data and apply a method covered in class. Use of longitudinal data is encouraged, but not required. The proposal will be an outline of the theory, background, and concepts of your intended project. On March 10 you will submit a 3-4 page analysis plan that briefly describes the data set, the variables, the method, and the model you propose (2 @ 5 points each = 10 points).
4) An in-class presentation of your research will be done with PowerPoint or equivalent software that produces professional quality graphics. This presentation will allow you to present what you have done as a work-in-progress and give you the opportunity to benefit from my (and class) comments before completing the final written paper. The presentation should simulate a conference presentation (depending on class size between 15-20 minutes). The quality of the in-class presentation will count toward 10 points. A full journal-formatted research paper, worth 40 points, will be due one week after the final class. The length of the paper should not exceed 25 pages with references, tables, and figures. (10 points + 40 points = 50 points).
The emphasis of this class is on preparing you to produce the highest quality research paper possible. Therefore, your workload will be distributed heavily toward the final paper. It is imperative to start this process early by thinking seriously about research questions and possible data sources during the first couple of weeks of class. Some students will use data they already have access to, while others will need to find their data sources. Students who need to find data will be given appropriate assistance, but also need to start early because finding, obtaining, and formatting data can be time consuming.
Course Outline and Reading Assignments
Jan 14 Introduction to the course
Short tutorial in SPSS-PC
If you are not familiar with SPSS-PC, consult SPSS for Windows: Brief Guide
University-sponsored instruction in SPSS for Windows is offered through CIT.
Data reduction: principal components and factor analysis
Applied readings:
Sung, KyuTaik (1995). Measures and dimensions of filial piety in Korea. Gerontologist. 35: 240247.
Tacq, J. (1997) Factor Analysis: The Investigation of Marital Adjustment, Multivariate Analysis Techniques in Social Science Research pp 266-289.
Jan 21 Holiday
Jan 28 Measurement models with latent variables
Reading: Maruyama: chapters 5, 7
Byrne: chapters 3,4,5 (optional)
Applied readings:
Mackinnon, A, McCallum, J., Andrews, G., & Anderson, I. (1998). The Center for Epidemiological Studies Depression Scale in Older Community Samples in Indonesia, North Korea, Myanmar, Sri Lanka, and Thailand. Journal of Gerontology: Psychological Sciences, 53, P343-P352.
Lynch, S. M. (2000). Measurement and Prediction of Aging Anxiety. Research on Aging, 22: 533-558.
Harford, T. C, Wechsler, H., & Muthén, B. O. (2003). Alcohol Related Aggression and Drinking at Off-Campus Parties and Bars: A National Study of Current Drinkers in College, Journal of Studies on Alcohol. 64: 704-711.
Feb 4 Path analysis: Introduction to causal models
Reading: Maruyama: chapters 1-3
Byrne: Chapter 1-2 (optional)
Applied reading:
Yates, M. E., Tennstedt, and Chang, B. (1999) Contributors to and Mediators of Psychological Well-Being for Informal Caregivers. Journal of Gerontology: Psychological Sciences 54B: P12-22.
Haridakis, P. M. & Rubin, A. M (2003). Motivation for Watching Television Violence and Viewer Aggression. Mass Communication & Society, 2003: 6: 29-56.
Musil, C.M., Jones, S. L., & Warner C. D. (1998) Structural Equation Modeling and Its
Relationship to Multiple Regression and Factor Analysis. Research in Nursing and Health, 21: 271-281
Feb 11 Structural equation models with latent variables
Reading: Maruyama, chapters 8-10
Byrne: chapter 6 (optional)
Applied reading:
Bahr, S. J. et. al. (1998) Family, Religiosity, and the Risk of Adolescent Drug Use. Journal of Marriage and the Family 60: 979-992.
Levin, J. S., L. M. Chatters, R. J. Taylor (1995). Religious Effects on Health Status and Life Satisfaction Among Black Americans. Journals of Gerontology: Social Sciences, 50B: S134-S163.
Zsembik, B.A. & Peek. K.M. (2001) Race Differences in Cognitive Functioning Among Older Adults. Journals of Gerontology: Psychological Sciences and Social Sciences.56B: S266-S274.
Feb 18 Holiday
Feb 25 Multiple-group structural equation modeling
Reading: Maruyama, 11
Byrne: 7, 8, 10 (optional)
Applied readings:
Bass, D. M. and M. J. McClendon, Deimling G.T., & Mukhergee, S. (1995) The Influence of a Diagnosed Mental Impairment on Family Caregiver Strain. Journal of Gerontology: Social Sciences, 49: S146-S155.
Keith, T., Keith, P. and Quirk, B. & Kimberly J. (1998). Longitudinal Effects of Parent Involvement on High School Grades: Similarities and Differences Across Gender and Ethnic Groups. Journal of School Psychology, 36: 335-63.
*Research paper proposals due - you will also give a short summary in class
Mar 3 Longitudinal models using SEM: Latent change and latent difference
Reading:
Maruyama, chapter 6
Applied reading:
Wickrama, K. A. S. et. al. (1997) Linking Occupational Conditions to Physical Health
through Marital, Social, and Intrapersonal Processes. Journal of Health and Social
Behavior. 38: 363-375.
Holahan, C. K & Chapman, J. R. (2002) Longitudinal Predictors of Proactive Goals and
Activity Participation at Age 80. Journals of Gerontology: Psychological Sciences.
57B: P418-P425.
Kelley-Moore, J. A. & Ferraro K. F.(2001) Functional Limitations and Religious Service
Attendance in Later Life: Barrier and/or Benefit Mechanism? Journals of
Gerontology: Social Sciences. 56B: S365-S373.
Mar 10 Latent growth curves using SEM
Reading:
Applied reading:
Walker, A.. J., Acock,, Bowman, and Fuzhong. (1996) Amount of Care Given and Caregiving Satisfaction: A Latent Growth Curve Analysis. Journals of Gerontology: PsychologicalSciences and Social Sciences. May 1996; Vol. 51B: P130P142.
Li, F., Duncan, T.E., McAuley E., Harmer P. & Smolkowski K. (2000). Didactic Example of Latent Curve Analysis Applicable to the Study of Aging. Journal of Aging and Health. 12: 388-425
Curran, P. and Bollen, K. Combining Autoregressive and Latent Curve Models. Chapter 4 in
New Methods for Analysis of Change (Collins & Sayer, Eds.)
*Research analysis plan due.
Mar 17 Spring Break
Mar 24 Hierarchical linear models: Contextual applications
Reading: Luke, pp. 1-52
Applied readings:
Taylor, M. C. (1998) How White Attitudes Vary with the Racial Composition of Local Populations: Numbers Count. American Sociological Review., 63: 512-535.
Takagi, E., Silverstein, M., & Crimmins, E. (2007) Intergenerational coresidence of older adults in Japan: Conditions for cultural plasticity. Journal of Gerontology: Social Sciences 62: S330-S339.
Mar 31 Hierarchical linear models: Growth curve applications
Reading: Luke, pp. 53-72,
Applied readings:
Cherlin, A., Chase-Lansdale, P. L., and McRae, C. (1998) Effects of Parental Divorce on Mental Health Throughout the Life Course., American Sociological Review, 63: 239-249.
Aber, Brown & Jones. (2003) Developmental Trajectories Toward Violence in Middle
Childhood: Course, Demographic Differences and Response to School-Based
Intervention. Developmental Psychology, 39: 324-348.
Silverstein, M., Conroy, S., Wang H, Giarrusso, R, & Bengtson, V.L. (2001).
Reciprocity in Parent-Child Relations Over the Adult Life Course.. Journal of
Gerontology: Social Sciences, 57, S3-S13.
April 7 Confirmatory classification analysis with latent classes and mixture modeling.
Reading: McCutcheon
Applied readings:
Silverstein, M. & Bengtson, V.L.. (1997). Intergenerational Solidarity and the Structure
of Adult Child-Parent Relationships in American Families. American Journal of
Sociology. 103: 429-460.
Muthén, B. & Muthén, Linda K, (2000). Integrating person-centered and variable-
centered analyses: Growth mixture modeling with latent trajectory classes.
Alcoholism: Clinical & Experimental Research. 24: 882-891
April 14 Solutions to Incomplete/Missing/Censored Data
Reading: Allison, Missing Data, pp. 1-40
Byrne, chapter 12. (optional)
Applied reading:
Freedman, V.A. & Wolfe, D.A. (1995) “A Case Study on the Use of Multiple
Imputation.” Demography. 32: 459-470.
Acock, Alan C. (working paper) “Working with Missing Values”
http://oregonstate.edu/~acock/missing/
How to make the most effective presentation of your research.
Apr 21 Presentations of final research projects
Apr 28 Presentations of final research projects
END OF SEMESTER
May 5 Final research papers due
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