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ANOVA Books

ANOVA Books. Intros Keppel, Geoffrey (1991), Design and Analysis: A Researcher’s Handbook (3 rd ed.), Englewood Cliffs, NY: Prentice Hall. Great intro, especially for non-quant people; i.e., lots of good verbal explanations

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ANOVA Books

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  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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 LioraPedhazurSchmelkin (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.

  6. 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.

  7. 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.

  8. 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.

  9. 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).

  10. 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.

  11. MANOVA Articles • Bird, Kevin D. and DusanHadzi-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.

  12. References: Power (Re: Sample Size) • Cohen, Jacob (1992), “A Power Primer,” Psychological Bulletin, 112 (1), 155-159. • Holland, Burt S. and Margaret DiPonzioCopenhaver (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), 328-337. • 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.

  13. 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.

  14. SAS Info • http://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.htm#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.

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