Bibliography

Here follows a list of academic references partly or wholly sympathetic to the guiding principle of the Society for the Suppression of the Correlation Coefficient. I have taken the liberty of including references that include standardization in other contexts (e.g., articles critical of standardized effect size in general).

Abelson, R. P. (1995). Statistics as principled argument. Hillsdale, NJ: Erlbaum.

Achen, C. H. (1977). Measuring representation: Perils of the correlation coefficient. American Journal of Political Science, 21, 805-815.

Baguley, T. (2004). Understanding statistical power in the context of applied research, Applied Ergonomics, 35, 73-80.

Baguley, T. (2009). Standardized or simple effect size: What should be reported? British Journal of Psychology. 100, 603-617.

Baguley, T. (2010). When correlations go bad … The Psychologist, 23, 122-3.

Baguley, T. (2012). Serious stats: A guide to advanced statistics for the behavioral sciences. Basingstoke: Palgrave.

Brand, A. (2011). Income inequality and the prevalence of mental illness: A note of caution. Journal of Epidemiology and Community Health. Retrieved from: http://jech.bmj.com/content/60/7/646/reply#jech_el_2839 on 23/9/12.

Bond, C.F., Jr., Wiitala, W.L., & Richard, F.D. (2003). Meta-analysis of raw mean effect size in analysis of variance. Psychological Methods, 5, 425-433.

Brillinger, D. R. (2001). John Tukey and the correlation coefficient, Computing Science and Statistics, 33. 204-218.

Cohen, P., Cohen, J., Aiken, L. S., & West, S. G. (1999). The problem of units and the circumstance for POMP. Multivariate Behavioral Research, 34, 315–346.

Dunlap, W. P, Cortina, J. M., Vaslow, J. B., & Burke, M. J. (1996). Meta-analysis of experiments with matched groups or repeated measures designs. Psychological Methods, 1, 170–177

Fern, Edward F. and Kent B. Monroe (1996), Effect Size Estimates: Issues and Problems in Interpretation, Journal of Consumer Research , 23, 89-105.

Fichman, M. (1999). Variance Explained: Why Size Doesn’t (Always) Matter. Research in Organizational Behavior, 21, 295-331.

Fisher, R. A. (1925). Statistical methods for research workers. London: Oliver & Boyd.

Freedman, D. A.  (2005). Linear statistical models for causation: A critical review. In B. Everitt and D. Howell (Eds.) The Wiley Encyclopedia of Statistics in Behavioral Science. New York: Wiley.

Frick, R. W. (1999). Defending the statistical status quo. Theory and Psychology, 9, 183-189.

Glass, G. V., McGaw, B., & Smith, M. L. (1981). Meta-analysis in CA: Sage.

Greenland S., Maclure M., Schlesselman J.J., Poole C., & Morgenstern H. (1991). Standardized regression coeficients: A further critique and review of some alternatives. Epidemiology, 2, 387-392. 

Greenland, S., Schlesselman, J. J., & Criqui, M. H. (1986). The fallacy of employing standardized regression coefficients and correlations as measures of effect. American Journal of Epidemiology, 123, 203-208. 

Kim, J.-Q, & Feree, G. D. (1981). Standardization in causal analysis. Sociological Methods & Research, 10, 187-210.

Lenth, R. V., 2001. Some practical guidelines for effective sample size determination. The American Statistician, 55:187-193.

Morris, S. B., & DeShon, R. P. (2002). Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs. Psychological Methods, 7, 105-125.

O’Grady, K. E., 1982. Measures of explained variance: cautions and limitations. Psychological Bulletin, 92:766-777.

Olejnik, S., & Algina, J. (2003). Generalized eta and omega squared statistics: Measures of effect size for some common research designs. Psychological Methods, 8, 434-447.

Robinson, D. H., Fouladi, R. T., Williams, N. J., & Bera, S. J. (2002). Some effects of providing effect size and “what if” information. Journal of Experimental Education, 70, 365-382.

Robinson, D. H., Whittaker, T., Williams, N., & Beretvas, S. N. (2003). It’s not effect sizes so much as comments about their magnitude that mislead readers. Journal of Experimental Education, 72, 51-64.

Simpson, A. (2018). Princesses are bigger than Elephants: effect size as a category error in evidence based education. British Educational Research Journal, 44(5), 897-913.

Simpson, A. (2017). The misdirection of public policy: comparing and combining standardised effect sizes. Journal of Education Policy, 32(4), 450-466.

Tukey, J. W. (1954). Causation, regression and path analysis. In O. Kempthorne, T. A. Bancroft, J. W. Gowen & J. L. Lush (Eds.), Statistics and mathematics in biology (pp. 35-66). Ames, IA: Iowa State College Press.

Tukey, J.W. (1969). Analyzing data: Sanctification or detective work? American Psychologist, 24, 83-91.

Wilkinson, L., & APA Task Force on Statistical Inference (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 594-604.