Transcript References - Vanderbilt Business School

ANOVA Books
Intros
•
Keppel, Geoffrey (1991), Design and Analysis: A Researcher’s Handbook (3rd ed.),
Englewood Cliffs, NY: Prentice Hall.
•
Great intro, especially for non-quant people; i.e., lots of good verbal
explanations
•
More recent: Keppel, Geoffrey and Thomas D. Wickens (2004), Design and
Analysis: A Researcher’s Handbook (4th ed.), Englewood Cliffs, NY: Prentice Hall.
•
Iversen, Gudmund R. and Helmut Norpoth (19xx), Analysis of Variance, Sage.
•
Succinct (I LOVE these little green Sage paperback primers!)
•
B. Hays, William L. (1988), Statistics (4th ed.), NY: Holt, Rinehart & Winston.
•
Kirk, Roger (1982), Experimental design: Procedures for the Behavioral sciences,
Belmont, CA: Brooks/Cole Publishing Co.
•
Snedecor, George W. and William G. Cochran (1980), Statistical Methods, (7th ed.),
Ames, IA: Iowa State University Press.
•
Scheffé, Henry (1959), The Analysis of Variance, NY: Wiley.
•
A little more “math-stat-y” (harder for some)
Also: Iacobucci, Dawn (1994). “Analysis of Experimental Data,” in Richard Bagozzi (ed.),
Principles of Marketing Research, Cambridge, MA: Blackwell, 224-278.
•
Inspired, what can I say.  If you can’t find it, email me and I’ll send you a copy.
ANCOVA (Analysis of Covariance)
•
•
•
Edwards, Allen L. (1979), Multiple Regression and the Analysis of Variance and
Covariance, NY: Freeman.
Wildt, A. R., and Ahtola, O. (1978), Analysis of Covariance, Beverly Hills, CA: Sage
Maxwell, Scott E., Harold D. Delaney, and Charles A. Dill (1984), “Another Look at
ANCOVA Versus Blocking,” Psych Bull, 95 (1), 136-147.
Experimental Design Books
Classics and reviewers will take these as high credibility:
•
Box, George E. P., J. Stuart Hunter, and William G. Hunter (2005), Statistics for
Experimenters: Design, Innovation, and Discovery 2nd ed., New York: Wiley.
•
Box, George E. P., William G. Hunter and J. Stuart Hunter (1978), Statistics for
Experimenters: An Introduction to Design, Data Analysis and Model Building, NY: Wiley.
•
Cochran, William G. and Gertrude M. Cox (1957), Experimental Designs, NY: Wiley.
•
Cox, D. R. (1958), Planning of Experiments, NY: Wiley.
•
Hicks, Charles R. (1982), Fundamental Concepts in the Design of Experiments 3rd ed.,
New York: CBS College Publishing.
•
Snedecor, George W. and William G. Cochran (1980) Statistical Methods 7th ed., Ames,
IA: The Iowa State University Press.
•
Winer, B. J., Donald R. Brown, Kenneth M. Michels (1991), Statistical Principles in
Experimental Design 3rd ed., NY: McGraw-Hill.
Experimental Design Books
Also very good:
• Berger, Paul D. and Robert W. Maurer (2002), Experimental Design: With Applications in
Management, Engineering, and the Sciences, Belmont, CA: Wadsworth.
• Brown, Steven R. and Lawrence E. Melamed (1990), Experimental Design and Analysis,
Newbury Park, CA: Sage.
• John, Peter W. M. (1971), Statistical Design and Analysis of Experiments, NY: Macmillan.
• Kirk, Roger E. (1982), Experimental Design: Procedures for the Behavioral Sciences (2nd
ed.), Belmont, CA: Brooks/Cole (pp.778-805).
• Rosenthal, Robert, and Ralph L. Rosnow (1991) Essentials of Behavioral Research:
Methods and Data Analysis 2nd ed., Boston, MA: McGraw-Hill.
• Spector, Paul E. (1981), Research Designs, Newbury Park, CA: Sage.
Experimental Design: Special Topics
•
•
•
•
•
•
•
Davison, Mark L. and Anu R. Sharma (1990), “Parametric Statistics and Levels of
Measurement: Factorial Designs and Multiple Regression,” Psychological Bulletin, 107
(3) 397-400.
Gardner, David M. and Russell W. Belk (1980), A Basic Bibliography on Experimental
Design in Marketing, Bibliography Series No.37, Chicago: AMA.
Hinkelmann, Klaus and Oscar Kempthorne (1994), Design and Analysis of Experiments,
Volume 1: Introduction to Experimental Design, NY: Wiley.
John, J. A. (1987), Cyclic Designs, London: Chapman & Hall.
Maxwell, Scott E. and Harold D. Delaney (1990) Designing Experiments and Analyzing
Data: A Model Comparison Perspective, Belmont, CA: Wadsworth.
Pedhazur, Elazar J. and Liora Pedhazur Schmelkin (1991), Measurement, Design, and
Analysis: An Integrated Approach, Hillsdale, NJ: Erlbaum.
Tabachnick, Barbara G. and Linda S. Fidell (2001), Computer-Assisted Research Design
and Analysis, Needham Heights, MA: Allyn & Bacon.
Experimental Designs
Quasi-Experimental Design:
• Campbell, Donald T. and Julian C. Stanley (1963) Experimental and Quasi-Experimental
Designs for Research, Chicago, IL: Rand McNally.
• Cook, Thomas D. and Donald T. Campbell (1979) Quasi-Experimentation: Design &
Analysis Issues for Field Settings, Boston, MA: Houghton Mifflin.
Within-Subjects Designs:
• Girden, Ellen R. (1992), ANOVA: Repeated Measures, Newbury Park, CA: Sage.
• Greenwald, Anthony G. (1976), “Within-Subjects Designs: To Use or Not To Use?,”
Psychological Bulletin, 83 (2), 314-320.
Random vs. Fixed Factors and Designs:
• Jackson, Sally and Dale E. Brashers. (1994), Random Factors in ANOVA, Thousand Oaks,
CA: Sage.
• & my review of that book in the Journal of Marketing Research 32 (May), 238-239.
•
Jaccard, James (1998), Interaction Effects in Factorial Analysis of Variance, Thousand
Oaks, CA: Sage.
References: Unbalanced Data (Unequal Cell n’s)
Unbalanced designs, missing data:
•
Little, Roderick J. A. and Donald B. Rubin (1987), Statistical Analysis with Missing Data,
NY: Wiley.
•
Schendel, U. (1989), Sparse Matrices: Numerical Aspects with Applications for Scientists
and Engineers, NY: Wiley.
•
Searle, S. R. (1987), Linear Models for Unbalanced Data, New York: Wiley.
•
Iacobucci, Dawn (1995), “The Analysis of Variance for Unbalanced Data,” in David W.
Stewart and Naufel J. Vilcassim (eds.), 1995 AMA Winter Educators’ Conference:
Marketing Theory and Applications, 6, Chicago: AMA, 337-343.
Sampling:
•
Kish, Leslie (1965), Survey Sampling, NY: Wiley.
•
Thompson, Steven K. (1992), Sampling, NY: Wiley.
Experimental Design: Managerial Articles
•
•
Almquist, Eric and Gordon Wyner (2001), “Boost Your Marketing ROI with Experimental
Design,” Harvard Business Review, 79 (9), 135-141.
Anderson, Eric T. and Duncan Simester (2011), “A Step-by-Step Guide to Smart Business
Experiments,” Harvard Business Review, 89 (3), 98-105.
Matrix Algebra: Books
Both of these books have excellent sections on matrix algebra:
•
Kirk, Roger E. (1982), Experimental Design: Procedures for the Behavioral Sciences (2nd
ed.), Belmont, CA: Brooks/Cole (pp.778-805).
•
Morrison, D. F. (1976), Multivariate Statistical Methods (2nd ed.), NY: McGraw-Hill
(pp.37-78).
MANOVA (Multivariate ANOVA) Books
•
•
Bray, James H. and Scott E. Maxwell (1985), Multivariate Analysis of Variance, Sage.
Manly, Bryan F. J. (1986), Multivariate Statistical Methods: A Primer, London & NY:
Chapman and Hall.
Chapters
• Harris (1985), “Chapter 3: Hotelling’s T2: Tests on One or Two Mean Vectors,” in his book,
A Primer of Multivariate Statistics.
• Most general “multivariate stats” books cover MANOVA also, albeit briefly.
MANOVA Articles
•
•
Bird, Kevin D. and Dusan Hadzi-Pavlovic (1983), “Simultaneous Test Procedures and the
Choice of a Test Statistic in MANOVA,” Psychological Bulletin, 93 (1), 167-178.
Hakstian, A. Ralph, J. Christian Roed, and John C. Lind (1979), “Two-Sample T2 Procedure
and the Assumption of Homogeneous Covariance Matrices,” Psychological Bulletin, 86
(6), 1255-1263.
References: Power (Re: Sample Size)
•
•
•
•
•
•
•
•
Cohen, Jacob (1992), “A Power Primer,” Psychological Bulletin, 112 (1), 155-159.
Holland, Burt S. and Margaret DiPonzio Copenhaver (1988), “Improved Bonferroni-Type
Multiple Testing Procedures,” Psychological Bulletin, 104 (1), 145-149.
Keselman, H. J., Paul A. Games, and Joanne C. Rogan (1980), “Type I and Type II Errors
in Simultaneous and Two-Stage Multiple Comparison Procedures,” Psychological
Bulletin, 98 (2), 356-358.
Kraemer, Helena Chmura and Sue Thiemann (1987), How Many Subjects?: Statistical
Power Analysis in Research, Newbury Park, CA: Sage.
Levine, Douglas W. and William P. Dunlap (1982), “Power of the F Test With Skewed
Data: Should One Transform or Not?,” Psychological Bulletin, 92, 272-280.
Maxwell, Scott E. and David A. Cole (1991), “A Comparison of Methods for Increasing
Power in Randomized Between-Subjects Designs,” Psychological Bulletin, 110 (2), 328337.
Ryan, T. A. (1980), “Comment on ‘Protecting the Overall Rate of Type I Errors for
Pairwise Comparisons With an Omnibus Test Statistic’,” Psychological Bulletin, 98 (2),
354-355.
Wahlsten, Douglas (1991), “Sample Size to Detect a Planned Contrast and a One
Degree-of-Freedom Interaction Effect,” Psychological Bulletin, 110 (3), 587-595.
References: Effect Sizes
•
•
•
Chow, Siu L. (1988), “Significance Test or Effect Size?,” Psychological Bulletin, 103 (1),
105-110.
O’Grady, Kevin E. (1982), “Measures of Explained Variance: Cautions and Limitations,”
Psychological Bulletin, 92 (3), 766-777.
Iacobucci, Dawn (2005), “On p-Values,” Journal of Consumer Research, 32 (1), 6-11.
SAS Info
•
http://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.h
tm#glm_toc.htm
•
SAS Institute (1990), SAS/STAT: User's Guide, Vol.2., Ver.6, 4th ed., Cary, NC: SAS
Institute Inc.
Freund, R. J., & R. C. Littell (1981), SAS for Linear Models: A Guide to the ANOVA and
GLM procedures, Cary, NC: SAS Institute.
•
•
SPSSX: Norusis, M. J. (1985), SPSSx: Advanced Statistics Guide, Chicago, IL: SPSS.