Psych. 711, Applied Multivariate Analysis
Fall, 2008
Dr. Hyde
Office hours: Thurs., 11:00-11:45 and by appt.
410 Brogden Psychology Bldg.
262-9522
jshyde@wisc.edu
Syllabus
Texts
Grimm, L. W., & Yarnold, P. R. (Eds.) (1995). Reading and understanding multivariate
statistics. Washington, DC: American Psychological Association.
Lipsey, M. W. & Wilson, D. B. (2001). Practical meta-analysis. Thousand Oaks, CA: Sage.
Stevens, J. (2002). Applied multivariate statistics for the social sciences 4th ed. Mahwah, NJ:
Erlbaum.
Journal articles are available from Learn@UW.
Books are available at A Room of One’s Own Bookstore, 307 W. Johnson St.
Other Relevant Texts
Gorsuch, R. L. (1983). Factor analysis. 2d ed. Hillsdale, NJ: Erlbaum.
SPSS for Windows: Base, Advanced Statistics
Tabachnick, B. G. & Fidell, L. S. (2001). Using multivariate statistics. 4th ed., New York:
Allyn & Bacon.
Classlist: psych711-1-f08@lists.wisc.edu
SCHEDULE
Week 1
Sept. 2
Week 2
Sept. 9
Introduction to multivariate statistical methods
Matrix algebra
Read: Grimm & Yarnold (G&Y) Ch. 1
Stevens, Chs. 1, 2
Multiple regression formulated in matrix terms
Cleaning data (see also
http://www.ats.ucla.edu/stat/sas/library/nesug99/ss123.pdf
Read: G&Y, Ch. 2
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Stevens, ch. 3 (read quickly)
Week 3
Sept. 16
Multivariate normal distribution, Wishart distribution; Hotelling's
T2, simple MANOVA
Read: G&Y, Ch. 8 to p. 267
Hummel & Sligo (1971)
Stevens, Ch. 4
Huberty & Morris (1989), Algina & Oshima (1990) (read them in
the order listed)
Week 4
Sept. 23
Complex MANOVA
Read: Stevens, Chs. 5, 6, 8
Olson (1976), Urberg et al. (1995)
Week 5
Sept. 30
Multivariate analysis of repeated measures data
Read: G&Y, Ch 8, p. 267-end
Stevens, Ch. 13
O’Brien & Kaiser (1985), Algina & Keselman (1997), Leichtman
& Ceci (1995) (in that order)
Week 6
Oct. 7
Discriminant analysis, MANCOVA
Read: G&Y, Ch. 9
Stevens Chs. 7, 9
Marche & Howe (1995)
Week 7
Oct. 14
EXAM 1: Multivariate analysis of variance
Introduction to meta-analysis
Read: G&Y, Ch. 10
Week 8
Oct. 21
Statistical methods in meta-analysis; methodological issues
Read: Lipsey & Wilson Chs 1-3
Grabe et al. (2008)
Week 9
Oct. 28
Meta-analysis of correlational data
Other issues: fixed vs. random-effects models; dichotomous
outcomes; factorial designs; power of moderator tests
Consultations on student meta-analysis projects
Read: Lipsey & Wilson Chs. 4-8
Week 10
Nov. 4
Introduction to factor analysis; principal components
Read: G&Y Ch 4
Week 11
Nov. 11
Issues in factor analysis: communalities, rotation, number of
factors
META-ANALYSIS PROJECTS DUE Nov. 11
Read: Stevens, Ch. 11 (through p. 415)
Zwick & Velicer (1986), McKinley & Hyde (1996)
Week 12
Nov. 18
Other factor-analytic models: maximum likelihood, confirmatory
analysis, 2- and 3-mode analysis, cluster analysis
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Read: York & John (1992), Fabrigar et al. (1999)
Week 13
Nov. 25
Catch up and review
Week 14
Dec. 2
EXAM 2: Factor analysis
Imputation for missing data
Read: Acock (2005)
Optional: Schafer & Graham (2002)
Canonical correlation
Optional: Shell & Husman (2008)
Week 15
Dec. 9
Course review
Practice final exam: choosing a multivariate method
Dec. 16
Take Home Final Exam, due by noon
GRADING
There will be a total of 500 possible points for the course. Each printout from a computer
assignment, done correctly and turned in on time, will count 10 points; points will be deducted
for lateness and/or inaccuracy. The matrix algebra homework will count 10 points. Each of the
two hourly exams will have 100 possible points. The meta-analysis project is worth a possible
100 points. The comprehensive final is worth 100 points.
COURSE OBJECTIVES
1. To gain an understanding of why and when one would use multivariate statistical methods,
including multivariate analysis of variance, factor analysis, and meta-analysis.
2. To develop skills in reading journal articles that present applications of multivariate methods
or advances in multivariate methods, e.g., articles in Psychological Bulletin (formerly) and
Psychological Methods (currently).
3. To develop skills in using computers to analyze multivariate data, to be able to interpret
printouts, and to be able to write up the results for a journal article.
4. To gain a basic (not necessarily advanced) understanding of the theoretical rationale and
derivations for multivariate statistics.
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REFERENCES
Journal Articles to Be Read in This Course (Learn@UW)
Acock, A. C. (2005). Working with missing values. Journal of Marriage and Family, 67,10121028.
Algina, J., & Keselman, H. J. (1997). Detecting repeated measures effects with univariate and
multivariate statistics. Psychological Methods, 2, 208-218.
Algina, J., & Oshima, T. C. (1990). Robustness of the independent samples Hotelling's T2 to
variance-covariance heteroscedasticity when sample sizes are unequal and in small ratios.
Psychological Bulletin, 108, 308-313.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use
of exploratory factor analysis in psychological research. Psychological Methods, 4, 272299.
Grabe, S., Ward., L. M., & Hyde, J. S. (2008). The role of the media in body image concerns
among women: A meta-analysis of experimental and correlational studies. Psychological
Bulletin, 134, 460-476.
Huberty, C. J., & Morris, J.D. (1989). Multivariate analysis versus multiple univariate analyses.
Psychological Bulletin, 105, 302-308.
Hummel, T. J., & Sligo, J. R. (1971). Empirical comparison of univariate and multivariate
analysis of variance procedures. Psychological Bulletin, 76, 49-57.
Leichtman, M. D. & Ceci, S. J. (1995). The effects of stereotypes and suggestions on
preschoolers' reports. Developmental Psychology, 31, 568-578.
Marche, T. A. & Howe, M. L. (1995). Preschoolers report misinformation despite accurate
memory. Developmental Psychology, 31, 554-567.
McKinley, N. M. & Hyde, J. S. (1996). The Objectified Body Consciousness Scale:
Development and validation. Psychology of Women Quarterly, 20, 181-216.
O’Brien, R. G., & Kaiser, M. K. (1985). MANOVA method for analyzing repeated measures
designs: An extensive primer. Psychological Bulletin, 97, 316-333.
Olson, C. L. (1976). On choosing a test statistic in multivariate analysis of variance.
Psychological Bulletin, 83, 579-586. (also see rejoinders following)
Shell, D. F. & Husman, J. (2008). Control, motivation, affect, and strategic self-regulation in the
college classroom: A multidimensional phenomenon. Journal of Educational Psychology, 100,
443-459.
Urberg, K. A., Degirmencioglu, S. R., Tolson, J. M., & Halliday-Scher, K. (1995). The structure
of adolescent peer networks. Developmental Psychology, 31, 540-547.
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York, K.L., & John, O.P. (1992). The four faces of Eve: A typological analysis of women's
personality at midlife. Journal of Personality and Social Psychology, 63, 494-508.
Zwick, W. R. & Velicer, W. F. (1986). Comparison of five rules for determining the number of
components to retain. Psychological Bulletin, 99, 432-442.
Other Relevant Articles
Bangert-Downs, R.L. (1986). Review of developments in meta-analytic method. Psychological
Bulletin, 99, 388-399.
Cliff, N. (1988). The eigenvalues-greater-than-one rule and the reliability of components.
Psychological Bulletin, 103, 276-279. (Disputes the statistical basis for Kaiser's rule for
the number of factors)
Fiske, D.W. (1983). The meta-analysis revolution in outcome research. Journal of Consulting
and Clinical Psychology, 51, 65-70.
Gillett, R. (2003). The metric comparability of meta-analytic effect-size estimators from factorial
designs. Psychological Methods, 8, 419-433.
Hakstian, A. R., Roed, J.C., & Lind, J.C. (1979). Two-sample T procedure and the assumption of
homogeneous covariance matrices. Psychological Bulletin, 86, 1255-1263. (addresses the
robustness of Hotelling's T2)
Hedges, L. V. & Pigott, T. D. (2001). The power of statistical tests in meta-analysis.
Psychological Methods, 6, 203-217.
Hedges, L. V., & Pigott, T. D. (2004). The power of statistical tests for moderators in metaanalysis. Psychological Methods, 9, 426-445.
Hedges, L. V. & Vevea, J. L. (1998). Fixed- and random-effects models in meta-analysis.
Psychological Methods, 3, 486-504.
Huberty, C.J. (1984). Issues in the use and interpretation of discriminant analysis.
Psychological Bulletin, 95, 156-171.
Keselman, H. J., Algina, J., Lix, L. M., Wilcox, R. R., & Deering, K. N. (2008). A generally
robust approach for testing hypotheses and setting confidence intervals for effect sizes.
Psychological Methods, 13, 110-129.
Kraemer, H.C., & Andrews, G. (1982). A nonparametric technique for meta-analysis effect size
calculation. Psychological Bulletin, 91, 404-412.
Morris, S. B. & DeShon, R. P. (1997). Correcting effect sizes computed from factorial analysis
of variance for use in meta-analysis. Psychological Methods, 2, 192-199.
Morris, S. B. & DeShon, R. P. (2002). Combining effect size estimates in meta-analysis with
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repeated measures and independent-groups designs. Psychological Methods, 7,
Orwin, R.G., & Cordray, D.S. (1985). Effects of deficient reporting on meta-analysis: A
conceptual framework and reanalysis. Psychological Bulletin, 97, 134-147.
Raudenbush, S.W., Becker, B.J., & Kalaian, H. (1988). Modeling multivariate effect sizes.
Psychological Bulletin, 103, 111-120.
Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological
Bulletin, 86, 638-661.
Rosenthal, R. (1995). Writing meta-analytic reviews. Psychological Bulletin, 118, 183-192.
Sánchez-Meca, J., Marín-Martínez, F., & Chacón-Moscoso, S. (2003). Effect-size indices for
dichotomized outcomes in meta-analysis. Psychological Methods, 8, 448-467.
Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art.
Psychological Methods, 7, 147-177.
Stevens, J. P. (1980). Power of the multivariate analysis of variance tests. Psychological Bulletin,
88, 728-737.
Stewart, D., & Love, W. (1968). A general canonical correlation index. Psychological Bulletin,
70, 160-163.
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I wish to include persons with disabilities fully in this course. Please let me know if you need
any special accommodations in the curriculum, instruction, or assessments of this course to
enable you to participate fully. I will try to maintain confidentiality of the information you share
with me.
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Occasionally a student may have a complaint about a T.A. or course instructor. If that
happens, you should feel free to discuss the matter directly with the T.A. or instructor. If the
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should discuss it with the course instructor. If the problem is not resolved to your satisfaction or
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email jpnewman@wisc.edu). You should also speak to the Department Chair if the complaint is
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because of your religion, race, gender, sexual orientation, or ethnic background, take your
complaint to the Office of Equity and Diversity (room 179-A Bascom Hall).
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