Please note that this syllabus should be regarded as only a general guide to the course. The instructor may have changed
specific course content and requirements subsequent to posting this syllabus. Last Modified: 15:11:09 08/26/2011
SC 704: Topics in Multivariate Statistics
Fall 2011
Tuesday/Thursday 3:00 – 4:15 pm
O’Neill 245
Professor: Sara Moorman
Office: 404 McGuinn Hall
Office hours: Mondays 1:15-3:15 pm or by appointment
E-mail: moormans@bc.edu
Phone: (617) 552 - 4209
About the Course
This applied course is designed for students in sociology, education, nursing, organizational
studies, political science, psychology, or social work with a prior background in statistics at the
level of SC703: Multivariate Statistics. It assumes a strong grounding in multivariate regression
analysis. The major topics of the course will include OLS regression diagnostics, binary,
ordered, and multinomial logistic regression, models for the analysis of count data (e.g., Poisson
and negative binomial regression), treatment of missing data, and the analysis of clustered and
stratified samples. All analyses in the course will be conducted using Stata, but no previous Stata
experience is necessary.
Readings
Required textbooks:
Enders, Craig K. 2010. Applied Missing Data Analysis. ISBN: 9781606236390
Long, J. Scott. 1997. Regression Models for Categorical and Limited Dependent Variables.
ISBN: 0803973748
Long, J. Scott and Jeremy Freese. 2006. Regression Models for Categorical Dependent
Variables Using Stata. 2nd ed. ISBN: 1597180114
Recommended textbook:
Acock, Alan C. 2010. A Gentle Introduction to Stata. 3rd ed. ISBN: 1597180750
Course reserves online:
Access “read for next week” entries that are not from the required purchases as .pdf files through
the library website (http://www.bc.edu/libraries/) or through the link on the course Blackboard
page (https://cms.bc.edu/webct/entryPageIns.dowebct).
SC 704 Topics in Multivariate Statistics
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Software
This course requires the use of the program Stata. The most current version is available on the
computers in the Sociology graduate student lounge. For use on your own computer, you have
two options: (1) access the program through remote connection to apps.bc.edu, or (2) purchase
the program through BC’s Research Services. Ask your department administrator about
Campuswide GradPlan. Prices start at $29 (price for a six-month student license).
Assessment
Grading scale
A
93 – 100%
B
83 – 86%
F
0 – 59%
Task
Article of the week
Project proposal
Project update I
Project update II
Presentation
Final paper draft
AB-
90 – 92%
80 – 82%
Due date
Weekly, Tuesdays (N = 10)
September 20
October 18
November 15
December 6 or 8
December 15
B+
C
87 – 89%
60 – 79%
Percentage of grade
10 at 1% each: 10%
10%
20%
20%
20%
20%
Article critique of the week
For each week, I’ve selected a recent publication from a major sociology journal that uses
a technique we’re covering in class that week. Their use of methods might be exemplary, or it
might leave you wondering why such a good journal accepted such a weak paper! Make a list of
what you think the authors did well and what they did poorly. In class we’ll discuss the article,
and you’ll submit your list to receive credit. I will simply note whether your work is complete or
incomplete rather than judge the content of your responses, so don’t worry if you don’t
understand every last thing the authors did. Bring your questions to class and we’ll work them
out. Because the purpose of this exercise is to prepare for class discussion, I will not accept late
work.
Specific questions to ask yourself while reading and listmaking include: Does this
analysis best answer the research question given the data the researchers had available, or is there
a discrepancy between the research question and its empirical operationalization? Would you
have chosen different statistics instead of or in addition to the statistics employed? Were you left
with any critiques of the data or methods, or did the authors anticipate your concerns? If you had
the data at hand, would you be able to replicate the analysis? Were the results interpreted clearly
and correctly? Were the results presented effectively in tables and/or figures? Are the
interpretations fair, or do they seem to go beyond what the data can really support?
Research project
I find that the best way to learn statistics is to practice them on real data that mean
something to you. Therefore, the major product of this course will be a journal-style research
article (i.e., 20-35 pages in length, including the standard sections: title page, abstract,
introduction, methods, results, discussion, references, tables/figures). The article is required to
SC 704 Topics in Multivariate Statistics
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include two or more of the methods covered in class from September 20 onward. For example,
you might run a test of mediation in a complex survey dataset, or one outcome that requires
binary logistic regression and a second that requires Poisson regression, or a multinomial logistic
regression on multiply-imputed data. (Neither using Stata for your analyses nor testing a simple
OLS regression model “count” towards your two methods.)
In mid-September you’ll submit a one or two page project proposal. In mid-October and
November you will submit written “updates” that will be drafts of sections of the paper. For
instance, for one update you might submit the introduction and methods sections, and for the
next update you might submit the results and discussion sections, or you might want me to look
at revisions of your introduction and methods sections. Precisely what you turn in will be up to
you, although I’m happy to make recommendations on a case-by-case basis. On December 6 or
8, you’ll give a conference-style presentation of your project in class, and on December 15,
you’ll submit your completed paper. Assignments submitted after 11:59 pm on their due dates
will be graded, but will assume a late penalty of 10 points per day.
Although it’s certainly not a requirement, you should seriously consider using this project
as an opportunity to meet a degree requirement (e.g., area exams), prepare a conference
presentation, and/or develop a submission for publication. If you’re already working on a project,
I encourage you to use this course to develop it. If you’re starting from scratch, many datasets
are publicly available from universities and government agencies, and many more are available
to researchers through BC’s subscription to the Inter-University Consortium for Political and
Social Research (ICPSR) at the University of Michigan. Be aware that the deadline to submit a
paper for presentation at ASA 2012 in Denver will be in mid-January, and your course paper will
fit their submission criteria.
Academic Honesty
Your work must be your words and ideas. When writing papers, use quotation marks around
someone else’s exact words and identify whose words they are. If you come across a good idea,
by all means use it in your writing, but be sure to acknowledge whose idea it is. Do not allow
another student to copy your work. Failure to comply will result in (a) automatic failure of the
assignment, and (b) a report to the Dean and the Committee on Academic Integrity. For further
information, please review the College’s policies on academic integrity here:
http://www.bc.edu/offices/stserv/academic/resources/policy.html#integrity
Schedule
September 6 and September 8
Lecture / Stata session topics

Sept. 6: Using Stata

Sept. 8: Locating and using data for secondary research, presented by Rani Dalgin and
Barbara Mento from BC Research Services
Read for next week

Long chapters 2 and 4
SC 704 Topics in Multivariate Statistics

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Long & Freese chapters 2 and 3
September 13 and September 15
Lecture / Stata session topic

Ordinary least squares (OLS) regression: Review and diagnostics
Read for next week

Glavin, Paul, Scott Schieman, and Sarah Reid. 2011. “Boundary-Spanning Work
Demands and Their Consequences for Guilt and Psychological Distress.” Journal of
Health and Social Behavior 52(1): 43-57.

Johnson, David R. and Lisa A. Elliott. 1998. “Sampling Design Effects: Do They Affect
the Analysis of Data from the National Survey of Family and Households?” Journal of
Marriage and Family 60(4): 993-1001.

Kreuter, Frauke and Richard Valliant. 2007. “A Survey on Survey Statistics: What Is
Done and Can Be Done in Stata.” Stata Journal 7(1): 1-21.

Winship, Christopher and Larry Radbill. 1994. “Sampling Weights and Regression
Analysis.” Sociological Methods and Research 23(2): 230-57.
To do for next week

Research project proposal

Assessment of Glavin, Schieman, and Reid
September 20 and September 22
Lecture / Stata session topic

Complex survey data
Read for next week

Baron, Reuben M. and David A. Kenny. 1986. “The Moderator-Mediator Variable
Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical
Considerations.” Journal of Personality and Social Psychology 51(6): 1173-82.

Hayes, Andrew F. 2009. “Beyond Baron and Kenny: Statistical Mediation Analysis in the
New Millennium.” Communication Monographs 76(4): 408-20.

MacKinnon, David P., Amanda J. Fairchild, and Matthew S. Fritz. 2007. “Mediation
Analysis.” Annual Review of Psychology 58: 593-614.
SC 704 Topics in Multivariate Statistics

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Staff, Jeremy, Angel Harris, Ricardo Sabates, and Laine Briddell. 2010. “Uncertainty in
Early Occupational Aspirations: Role Exploration or Aimlessness?” Social Forces, 89(2):
659-84.
To do for next week

Assessment of Staff, Harris, Sabates, and Briddell
September 27 and September 29
Lecture / Stata session topic

Mediation
Read for next week

Fairchild, Amanda J. and Samuel D. McQuillin. 2010. “Evaluating Mediation and
Moderation Effects in School Psychology: A Presentation of Methods and Review of
Current Practice.” Journal of School Psychology 48: 53-84.

Schmutz, Vaughn, and Alison Faupel. 2010. “Gender and Cultural Consecration in
Popular Music.” Social Forces 89(2): 685-708.

Wu, Amery D. and Bruno D. Zumbo. 2008. “Understanding and Using Mediators and
Moderators.” Social Indicators Research 87: 367-92.
To do for next week

Assessment of Schmutz and Faupel
October 4 and October 6
Lecture / Stata session topic

Moderation
Read for next week

Enders chapters 1, 2, and 10

Robnett, Belinda and Cynthia Feliciano. 2011. “Patterns of Racial/Ethnic Exclusion by
Internet Daters.” Social Forces 89(3): 807-828.
To do for next week

Assessment of Belinda and Feliciano
SC 704 Topics in Multivariate Statistics
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October 11 and October 13
Lecture / Stata session topic

Missing data
Read for next week

Enders chapters 7, 8, and 9

Schafer, Markus H. and Tetyana Pylypiv Shippee. 2010. “Age Identity in Context: Stress
and the Subjective Side of Aging.” Social Psychology Quarterly 73(3): 245-64.
To do for next week

Assessment of Schafer and Shippee

Project update I
October 18 and October 20
Lecture / Stata session topic

Missing data
Read for next week

Long chapter 3

Long & Freese chapter 4

Williams, Kirk R. and Nancy G. Guerra. 2011. “Perceptions of Collective Efficacy and
Bullying Perpetration in Schools.” Social Problems 58(1): 126-43.
To do for next week

Assessment of Williams and Guerra
October 25 and October 27
Lecture / Stata session topic

Binary outcomes
Read for next week

Long chapter 5

Long & Freese chapter 5

Bailey, Amy Kate, Stewart E. Tolnay, E. M. Beck, and Jennifer D. Laird. Forthcoming.
“Targeting Lynch Victims: Social Marginality or Status Transgressions?” American
Sociological Review.
SC 704 Topics in Multivariate Statistics
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To do for next week

Assessment of Bailey, Tolnay, Beck, and Laird
November 1 and November 8
***Note: No class November 3 due to home football game***
Lecture / Stata session topic

Ordinal outcomes
Read for next week

Long chapter 6

Long & Freese chapters 6 and 7

Coverdill, James E., Carlos A. Lopez, and Michelle A. Petrie. 2011. “Race, Ethnicity,
and the Quality of Life in America, 1972-2008.” Social Forces 89(3): 783-806.
To do for next week

Assessment of Coverdill, Lopez, and Petrie
November 10 and November 15
Lecture / Stata session topic

Nominal outcomes
Read for next week

Buchmann, Claudia, Dennis J. Condron, and Vincent J. Roscigno. 2010. “Shadow
Education, American Style: Test Preparation, the SAT, and College Enrollment.” Social
Forces 89(2): 435-62. (has commentaries and rejoinder; see separate .pdf files by Sigal
Alon, Eric Grodsky, and Claudia Buchmann)

Anderton, Douglas T. and Eric Cheney. 2009. “Log-Linear Analysis.” Pp. 285-306 in The
Handbook of Data Analysis, edited by M. A. Hardy and A. Bryman. Thousand Oaks, CA:
Sage.

Long chapter 9 section 5 only
To do for next week

Research project update II

Assessment of Buchmann, Condron, and Roscigno
SC 704 Topics in Multivariate Statistics
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November 17
Lecture / Stata session topic

Log-linear analysis
To read for 11/29

Long & Freese chapter 8

Long chapter 8
November 22
Informal peer review of sections of one another’s papers
November 24
No class; happy Thanksgiving!
November 29 and December 1
Lecture topic

Count data
To read for next week

Faris, Robert and Diane Felmlee. 2011. “Status Struggles: Network Centrality and
Gender Segregation in Same and Cross Gender Aggression.” American Sociological
Review 76(1): 48-73.
To do for next week

Assessment of Faris and Felmlee
December 6 and December 8
Class presentations
December 15
Final paper draft due by 11:59 pm
SC 704 Topics in Multivariate Statistics
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Additional sources, for your reference
On Stata:
o Acock book
o Stata Journal
o The Getting Started with Stata (Mac, Unix, and Windows versions) manuals, available
for loan at O’Neill or for purchase at http://www.stata.com/bookstore/gs.html
o Stata User’s Guide, available for loan at O’Neill or for purchase at
http://www.stata.com/bookstore/guide.html
o Resources to help you learn and use Stata: http://www.ats.ucla.edu/stat/stata/
o SPost: Postestimation analysis with Stata: http://www.indiana.edu/~jslsoc/spost.htm
Relevant titles in the “little green” Sage series:
o Allison, Paul D. 2001. Missing Data.
o Berry, William D. 1993. Understanding Regression Assumptions.
o Borooah, Vani K. 2002. Logit and Probit: Ordered and Multinomial Models.
o Fox, John. 1991. Regression Diagnostics.
o Iacobucci, Dawn. 2008. Mediation Analysis.
o Ishii-Kuntz, Masako. 1994. Ordinal Log-Linear Models.
o Jaccard, James and Robert Turrisi. 2003. Interaction Effects in Multiple Regression.
o Knoke, David and Peter J. Burke. 1980. Log-Linear Models.
o Lee, Eun Sul and Ronald N. Forthofer. 2006. Analyzing Complex Survey Data.
o Liao, Tim Futing. 1994. Interpreting Probability Models.
o Menard, Scott. 1995. Applied Logistic Regression Analysis.
o O’Connell, Ann A. 2005. Logistic Regression Models for Ordinal Response Variables.
Sage.
o Pampel, Fred C. 2000. Logistic Regression: A Primer.
Full-length textbooks:
o Afifi, Abdelmonem, Virginia A. Clark, and Susanne May. 2004. Computer-Aided
Multivariate Analysis, 4th Edition. Chapman & Hall.
SC 704 Topics in Multivariate Statistics
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o Cameron, A. Colin, and Pravin K. Travedi. 1998. Regression Analysis of Count Data.
Cambridge University Press.
o Heeringa, Steven G., Brady T. West, and Patricia A. Berglund. 2010. Applied Survey
Data Analysis. CRC Press.
o Hilbe, Joseph M. 2009. Logistic Regression Models. Taylor & Francis.
o Little, Roderick J. and Donald B. Rubin. 2002. Statistical Analysis with Missing Data, 2nd
Edition. New York, NY: Wiley.
o Matthews, David E. and Vernon T. Farewell. 2007. Using and Understanding Medical
Statistics. Karger.
o Powers, Daniel A. and Yu Xie. 2000. Statistical Methods for Categorical Data Analysis
Academic Press.
o Woolridge, Jeffrey M. 2002. Econometric Analysis of Cross Section and Panel Data.
MIT Press.
On the web:

Least squares:
http://hadm.sph.sc.edu/COURSES/J716/demos/LeastSquares/LeastSquaresDemo.html

PRODCLIN: http://www.public.asu.edu/~davidpm/ripl/Prodclin/

Mediation: http://www.public.asu.edu/~davidpm/ripl/mediate.htm

Moderation: An introduction: http://davidakenny.net/cm/moderation.htm

Statistical power calculators:
http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/PowerSampleSize
http://www.danielsoper.com/statcalc/default.aspx#c17
http://www.psycho.uni-duesseldorf.de/aap/projects/gpower/
Other books, chapters, and articles:

Acock, Alan C. 2005. “Working with Missing Values.” Journal of Marriage and Family
67(4): 1012-28.

Cohen, Jacob. 1994. “The Earth Is Round (p < .05).” American Psychologist 49: 9971003.
SC 704 Topics in Multivariate Statistics
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Coxe, Stefany, Stephen G. West, and Leona S. Aiken. 2009. “The Analysis of Count
Data: A Gentle Introduction to Poisson Regression and its Alternatives.” Journal of
Personality Assessment 91(2): 121-36.

Fullerton, Andrew S. 2009. “A Conceptual Framework for Ordered Logistic Regression
Models.” Sociological Methods and Research 38(2): 306-47.

Hoffman, Saul D. and Greg J. Duncan. 1988. “Multinomial and Conditional Logit
Discrete-Choice Models in Demography.” Demography 25(3): 415-27.

Little, Roderick J. 1988. “A Test of Missing Completely at Random for Multivariate Data
with Missing Values.” Journal of the American Statistical Association 83: 1198-202.

MacKinnon, David P., Chondra M. Lockwood, Jeanne M. Hoffman, Stephen G. West,
and Virgil Sheets. 2002. “A Comparison of Methods to Test Mediation and Other
Intervening Variable Effects.” Psychological Methods 7: 83-104.

McFadden, Daniel. 1973. “Conditional Logit Analysis of Qualitative Choice Behavior.”
Pp. 105-42 in P. Zarembka (Ed.), Frontiers of Econometrics, New York, NY, Academic
Press.

Miller, Jane E. 2005. The Chicago Guide to Writing about Multivariate Analysis.
University of Chicago Press. ***Highly recommended!***

Peng, Chao-Ying Joanne, Kuk Lida Lee, and Gary M. Ingersoll. 2002. “An Introduction
to Logistic Regression Analysis and Reporting.” The Journal of Education Research
96(1): 3-14.

Raftery, Adrian E. 1995. “Bayesian Model Selection in Social Research.” Sociological
Methodology 25: 111-63.