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Readings for Students in Graduate Statistics

Howell Chapters 1 and 2, The Basics

  1. Aiken, L. S., West, S. G., & Millsap, R. E.  (2008).  Doctoral training in statistics, measurement, and methodology in psychology.  American Psychologist, 63, 32-50.  doi: 10.1037/0003-066X.63.1.32 
  2. DeCarlo, L. T. (1997). On the meaning and use of kurtosis. Psychological Methods, 2, 292-307. 
  3. Gaito, J. (1980). Measurement scales and statistics: Resurgence of an old misconception. Psychological Bulletin, 87, 564-567. 

Research Design

  1. Begley, S.  (2008, August 25).  Coddling human guinea pigs.  Newsweek, 14.
  2. Mook, D. G. (1983). In defense of external invalidity. American Psychologist, 38, 379-387. 

Howell Chapter 4, Basics of Inferential Statistics

  1. Cowles, M., & Davis, C. (1982). On the origins of the .05 level of statistical significance. American Psychologist, 37, 553-558. 
  2. Wainer, H.  (2007).  The most dangerous equation.  American Scientist, 95, 249-256. 

Howell Chapter 7, Student's t

Robustness, Ignorant Experts, and the Psychology of Publication

  1. Bradley, J. V. (1982). The insidious L-shaped distribution. Bulletin of the Psychonomic Society, 20, 85-88.   
  2. Bradley, J. V. (1984). The complexity of nonrobustness effects. Bulletin of the Psychonomic Society, 22, 250-253.   
  3. Bradley, J. V. (1981). Overconfidence in ignorant experts. Bulletin of the Psychonomic Society, 17, 82-84.   
  4. Bradley, J. V. (1981). Pernicious publication practices. Bulletin of the Psychonomic Society, 18, 31-34.   
  5. Bradley, J. V. (1982). Editorial overkill. Bulletin of the Psychonomic Society, 19, 271-274.   
  6. Bradley, J. V. (1984). Antinonrobustness: A case study in the sociology of science. Bulletin of the Psychonomic Society, 22, 463-466.   
  7. Kruger, J., & Dunning, D.  (1999).  Unskilled and unaware of it:  How difficulties in recognizing one's own incompetence lead to inflated self-assessments.  Journal of Personality and Social Psychology, 77, 1121-1134.
  8. Online Discussion of Ignorant Experts.
  9. Black, S., & Wuensch, K. L. (2003). Two Case Studies in the Ethics of Scientific Publication.

Meta Analysis and Effect Size

  1. Coulson, M., Healey, M., Fidler, F., & Cumming, G.  (2010).  Confidence intervals permit, but don't guarantee, better inference than statistical significance testing.  Frontiers in Quantitative Psychology and Measurement, 1:26. doi:10.3389/fpsyg.2010.00026
  2. Eagly, A. H. (1987). Reporting sex differences. American Psychologist, 42, 756-757.  
  3. Hyde, J. S. (1981). How large are cognitive gender differences? American Psychologist, 36, 892-901.   
  4. Rosenthal, R. (1990). How are we doing in soft psychology? American Psychologist, 45, 775-777. 
  5. Rosenthal, R., & Rubin, D. B. (1982). Further meta-analytic procedures for assessing cognitive gender differences. Journal of Educational Psychology, 74, 708-712. 

Howell Chapter 8, Power

  1. Aberson, C.  (2002).  Interpreting null results:  Improving presentation and conclusions with confidence intervals.  Journal of Articles in Support of the Null Hypothesis, 1, 36-42.
  2. American Psychological Association. (2001). Task Force on Statistical Inference Initial Report
  3. Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159.  
  4. Hoenig, J. M., & Heisey, D. M.  The abuse of power:  The pervasive fallacy of power calculations for data analysis.  The American Statistician, 55, 19-24.  
  5. Huberty, C. J. (1987). On statistical testing. Educational Researcher, 16,  4 - 9. 
  6. Nelson, N., Rosenthal, R., & Rosnow, R. L. (1986). Interpretation of significance by psychological researchers. American Psychologist, 41, 1299-130l.  
  7. Nickerson, R. S. (2000). Null hypothesis significance testing: A review of an old and continuing controversy. Psychological Methods, 5 241-301.  
  8. Rosnow, R. L., & Rosenthal, R. (1989). Statistical procedures and the justification of knowledge in psychological science. American Psychologist, 44, 1276-1284. 
  9. Schmidt, F. L. (1996). Statistical significance testing and cumulative knowledge in psychology: Implications for training of researchers. Psychological Methods, 1, 115-129. 
  10. Tachibana, T. (1980). Persistent erroneous interpretation of negative data and assessment of statistical power. Perceptual & Motor Skills, 51, 37-38. 
  11. Wilkinson, L., & Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 594-604. Read a summary of this article – Read the article online. 
  12. Wuensch, K. L. (1994). Evaluating the relative seriousness of type I versus type II errors in classical hypothesis testing. In B. Brown (Ed.), Disseminations of the International Statistical Applications Institute: Vol 1 (3rd ed., pp. 76-79). Wichita, KS: ACG Press. Available at http://core.ecu.edu/psyc/wuenschk/StatHelp/Type-I-II-Errors.htm.
  13. Wuensch, K. L. (1987). Frequency of type I errors in professional journals. Unpublished manuscript available at http://core.ecu.edu/psyc/wuenschk/StatHelp/Type1.htm.

Howell Chapter 9, Bivariate Correlation and Regression

  1. MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7, 19-40. 
  2. Wuensch, K. L. et al.  Dichotomizing Continuous Variables: A Bad Idea.

Howell Chapter 12, Multiple Comparisons Among Means

  1. Perneger, T. V.  (1998).  What's wrong with Bonferroni adjustments.  BMJ, 316, 1236-1238. 
  2. Ryan, T. A. (1959). Comments on orthogonal components. Psychological Bulletin, 56, 394-396. 

Howell Chapters 13 & 16, Factorial ANOVA

  1. Bickel, P. J., Hammel, E. A., & O'Connell, J. W.  (1975).  Sex bias in graduate admissions:  Data from Berkeley.  Science, 187, 398-404.  – example of a reversal paradox.
  2. Howell, D. C. & McConaughy, S. H. (1982). Nonorthogonal analysis of variance: Putting the question before the answer. Educational and Psychological Measurement, 42, 9-24. – Least Squares ANOVA.   
  3. Johnson, B. G., & Beck, H. P. (1988). Strict and lenient grading scales: How do they affect the performance of college students with high and low SAT scores? Teaching of Psychology, 15, 127-131. ( Example of factorial ANOVA)
  4. Messic, D. M. & van de Geer, J. P. (1981). A reversal paradox. Psychological Bulletin, 90, 582-593. 

Howell Chapter 17, Multidimensional Contingency Tables

  1. Meyers, A. W., Stunkard, A. J., Coll, M., & Cooke, C. J. (1980). Stairs, escalators, and obesity. Behavior Modification, 4, 355-359. (Source of the data used in the document Three-Way Nonhierarchical Log-Linear Analysis: Escalators and Obesity). 

Howell Chapter 18, Nonparametrics

  1. Lamb, G. S. (1984). What you always wanted to know about six but were afraid to ask. Journal of Irreproducible Results, 29(3), 18-20.
  2. Wuensch, K. L., & Cooper, A. J. (1981). Preweaning paternal presence and later aggressiveness in male Mus musculus. Behavioral and Neural Biology, 32, 510-515. (Example of nonparametric analysis)

Introduction to Multivariate Statistics

  1. Aziz, S., & Zickar,  M. J.  (2006).  A cluster analysis investigation of workaholism as a syndrome. Journal of Occupational Health Psychology, 11, 52-62.  (Example of cluster analysis). 
  2. Chia, R. C., Wuensch, K. L., Childers, J., Chuang, C., Cheng, B., Cesar-Romero, J., & Nava, S. (1994). A comparison of family values among Chinese, Mexican, and American college students. Journal of Social Behavior and Personality, 9, 249-258. (Example of principal components analysis)
  3. Greenwald, A. G., & Gillmore, G. M. (1997). No pain, no gain? The importance of measuring course workload in student ratings of instruction. Journal of Educational Psychology, 89, 743-751.  (Example of structural equation modeling).  
  4. McCammon, S., Golden, J., & Wuensch, K. L. (1988). Predicting course performance in freshman and sophomore physics courses: Women are more predictable then men. Journal of Research in Science Teaching, 25, 501-510. (Example of multiple correlation/regression)
  5. Moore, C. H., Wuensch, K. L., Hedges, R. M., & Castellow, W. A. (1994). The effects of physical attractiveness and social desirability on judgments regarding a sexual harassment case. Journal of Social Behavior and Personality, 9, 715-730. (Example of log-linear analysis of multidimensional contingency table)
  6. Patel, S., Long, T. E., McCammon, S. L., & Wuensch, K. L. (1995). Personality and emotional correlates of self-reported antigay behaviors. Journal of Interpersonal Violence, 10, 354-366. (Example of canonical correlation/regression)
  7. Poulson, R. L., Braithwaite, R. L., Brondino, M. J., & Wuensch, K. L. (1997). Mock jurors' insanity defense verdict selections: The role of evidence, attitudes, and verdict options. Journal of Social Behavior and Personality, 12, 743-758.   (Example of discriminant function analysis)
  8. Wuensch, K. L. (1992). Fostering house mice onto rats and deer mice: Effects on response to species odors. Animal Learning and Behavior, 20, 253-258. (Example of doubly multivariate repeated measures ANOVA)
  9. Wuensch, K. L., Chia, R. C., Castellow, W. A., Chuang, C.-J., & Cheng, B.-S. (1993). Effects of physical attractiveness, sex, and type of crime on mock juror decisions: A replication with Chinese students. Journal of Cross-Cultural Psychology, 24, 414-427. (Example of MANOVA).  
  10. Wuensch, K. L., & Poteat, G. M. (1998). Evaluating the morality of animal research: Effects of ethical ideology, gender, and purpose. Journal of Social Behavior and Personality, 13, 139-150.  (Example of logistic regression and ANCOV)

Multiple Regression

  1. MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D.  (2002).  On the practice of dichotomization of quantitative variables.  Psychological Methods, 7, 19-40. 
  2. Poteat, G. M., Wuensch, K. L., & Gregg, N. B. (1988). An investigation of differential prediction with the WISC-R. Journal of School Psychology, 26, 59-68.  (Example of Potthoff analysis).
  3. Smith, R. L., Ager, J. W., Jr., & Williams, D. L.  (1992).  Suppressor variables in multiple regression/correlation.  Educational and Psychological Measurement, 52, 17-29. 
  4. Thompson, B.  (1995).  Stepwise regression and stepwise discriminant analysis need not apply here:  A guidelines editorial.  Educational and Psychological Measurement, 55:  525-534. 
  5. Wuensch, K. L., & Poteat, G. M. (1998). Evaluating the morality of animal research: Effects of ethical ideology, gender, and purpose. Journal of Social Behavior and Personality, 13, 139-150.  (Example of logistic regression)

Factor Analysis and Principal Components Analysis

  1. Dabbs, J. M., Jr., & Ruback, R. B. (1988). Saliva testosterone and personality of male college students. Bulletin of the Psychonomic Society, 26, 244-247. (Example of factor analysis) 
  2. Davis, M. A., Anderson, M. G., & Curtis, M. B.  (2001).  Measuring ethical ideology in business ethics: A critical analysis of the Ethics Position
    Questionnaire.  Journal of Business Ethics, 32,  35-53.  (Example of Confirmatory Factor Analysis) 
  3. Forsyth, D.R.  (1980). A taxonomy of ethical ideologies, Journal of Personality and Social Psychology, 39, 175-184.  (Example of Exploratory Factor Analysis) 
  4. Ossenkopp, K.-P., & Mazmanian, D. S. (1985). Some behavioral factors related to the effects of cold-restraint stress in rats: A factor analytic-multiple regression approach. Physiology and Behavior, 34, 935-941. (Example of principal components analysis). 
  5. Redfern, K., & Crawford, J.  (2004).  An empirical investigation of the ethics position questionnaire in the People's Republic of China.  Journal of Business Ethics, 50, 199-210.   (Example of Exploratory Factor Analysis) 
  6. Shen, L.,  Condit, C. M., & Wright, L.  (2009).  The psychometric property and validation of a fatalism scale.  Psychology and Health, 24, 597–613.  doi: 10.1080/08870440801902535  (Example of Confirmatory Factor Analysis) 
  7. Wuensch, K. L. (2001). Review of Article on Use of Exploratory Factor Analysis.

MANOVA/DFA

  1. Castellow, W. A., Wuensch, K. L., & Moore, C. H. (1990). Effects of physical attractiveness of the plaintiff and defendant in sexual harassment judgments. Journal of Social Behavior and Personality, 5, 547-562. (Example of MANOVA and logit analysis)
  2. Harris, C. R. (2000). Psychophysiological responses to imagined infidelity: The specific innate modular view of jealousy reconsidered. Journal of Personality and Social Psychology, 78, 1082-1091. (This article serves as an example of use of MANOVA as well as use of power analysis, confidence intervals, and appropriate use of the first person in scientific writing.) 
  3. Huberty, C. J., & Barton, R. M. (1989). An introduction to discriminant analysis. Measurement and Evaluation in Counseling and Development, 22, 158-168. 
  4. Huberty, C. J., & Morris, J. D. (1989). Multivariate analysis versus univariate analyses. Psychological Bulletin, 105, 302-308. 
  5. Poulson, R. L., Braithwaite, R. L., Brondino, M. J., & Wuensch, K. L. (1997). Mock jurors' insanity defense verdict selections: The role of evidence, attitudes, and verdict options. Journal of Social Behavior and Personality, 12, 743-758.   (Example of Discriminant Function Analysis)

Path Analysis

  1. Ingram, K. L., Cope, J. G., Harju, B. L., & Wuensch, K. L. (2000). Applying to graduate school: A test of the theory of planned behavior. Journal of Social Behavior and Personality, 15, 215-226.  (Example of path analysis)
  2. Keith, T. Z., Pottebaum, S. M., & Eberhart, S. (1986). Effects of self-concept and locus of control on academic achievement: A large sample path analysis. Journal of Psychoeducational Assessment, 4, 61-72. 
  3. Keith, T. Z., Reimers, T. M., Fehrmann, P. G., Pottebaum, S. M., & Aubey, L. W. (1986). Parental involvement, homework, and TV time: Direct and indirect effects on high school achievement. Journal of Educational Psychology, 78, 373-380. 
  4. Keith, T. Z., Harrison, P. L., & Ehly, S. W. (1987). Effects of adaptive behavior on achievement: Path analysis of a national sample. Professional School Psychology, 2, 205-215. 
  5. Keith, T. Z. (1988). Path analysis: An introduction for school psychologists. School Psychology Review, 17, 343-362.  
  6. Keith, T. Z. (1988). Using path analysis to test the importance of manipulable influences on school learning. School Psychology Review, 17, 637-643.

Hierarchical (Multilevel) Linear Modeling

  1. Singer, J. D.  (1998).  Using SAS PROC MIXED to fit multilevel models, hierarchical models, and individual growth models.  Journal of Educational and Behavioral Statistics, 24, 323-355.  

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