Psych. 711, Applied Multivariate Analysis

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 [email protected]

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: [email protected]

SCHEDULE Week 1 Sept. 2 Introduction to multivariate statistical methods Matrix algebra Read: Grimm & Yarnold (G&Y) Ch. 1 Stevens, Chs. 1, 2 Week 2 Sept. 9 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

1 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)

2 Week 12 Nov. 18 Other factor-analytic models: maximum likelihood, confirmatory analysis, 2- and 3-mode analysis, cluster analysis 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.

3 REFERENCES Journal Articles to Be Read in This Course (Learn@UW) Acock, A. C. (2005). Working with missing values. Journal of Marriage and Family, 67,1012- 1028. 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, 272- 299. 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.

4 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 meta- analysis. 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

5 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. *****

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.

Where to take complaints about a Teaching Assistant or Course Instructor: 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 complaint is about the T.A. and you do not feel comfortable discussing it with him or her, you should discuss it with the course instructor. If the problem is not resolved to your satisfaction or you do not want to approach the instructor, make an appointment to see the Chair of the Psychology Department, Professor Joseph Newman (room 238 Psychology, phone 262-1040, email [email protected]). You should also speak to the Department Chair if the complaint is about the instructor and you do not feel comfortable discussing it directly with him or her.

If your complaint has to do with sexual harassment, please contact Susan Gallagher, Psychology Department Administrator (room 218 Psychology, phone 262-1042, email [email protected]). If you believe the T.A. or course instructor has discriminated against you

6 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).