Better statistics for better decisions: Rejecting null hypotheses statistical tests in favor of replication statistics

Psychology in the Schools

Volumn 44, Issue 5, 2007, Pages 471-481

  Sanabria, Federico ^a   Killeen, Peter R ^a  

^a ARIZONA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34250862693     PISSN: 00333085     EISSN: 15206807     Source Type: Journal    
DOI: 10.1002/pits.20239     Document Type: Article

References (21)

1. Cortina, J.M., & Nouri, H. (2000). Effect size for ANOVA designs. Thousand Oaks, CA: Sage.
2. Gumming, G., & Finch, S. (2001). A primer on the understanding, use and calculation of confidence intervals based on central and noncentral distributions. Educational and Psychological Measurement, 61, 532-575.
3. Doros, G., & Geier, A.B. (2005). Comment on "An alternative to null hypothesis significance tests." Psychological Science, 16, 1005-1006.
4. Estes, W.K. (1997). On the communication of information by displays of standard errors and confidence intervals. Psychonomic Bulletin & Review, 4, 330-341.
5. Fisher, R.A. (1959). Statistical methods and scientific inference. New York: Hafner.
6. Hedges, L.V., & Olkin, I. (1985). Statistical methods for meta-analysis. New York: Academic Press.
7. Killeen, P.R. (2005a). An alternative to null hypothesis significance tests. Psychological Science, 16, 345-353.
8. Killeen, P.R. (2005b). Replicability, confidence, and priors. Psychological Science, 16, 1009-1012.
9. Killeen, P.R. (2005c). Tea-tests. The General Psychologist, 40, 16-19.
10. Killeen, P.R. (2006). Beyond statistical inference: A decision theory for science. Psychonomic Bulletin & Review, 13, 549-569.
11. Killeen, P.R. (in press). The probability of replication: Its logic, justification, and calculation. In J.W. Osborne (Ed.), Best practices in quantitative methods. Thousand Oaks, CA: Sage.
12. Linares, L.O., Rosbruch, N., Stern, M.B., Edwards, M.E., Walker, G., Abikoff, H.B., et al. (2005). Developing cognitive-social-emotional competencies to enhance academic learning. Psychology in the Schools, 42, 405-417.
13. Macdonald, R.R. (2005). Why replication probabilities depend on prior probability distributions. A rejoinder to Killeen (2005). Psychological Science, 16, 1007-1008.
14. Maurer, B. A. (2004). Models of scientific inquiry and statistical practice: Implications for the structure of scientific knowledge. In M.L. Taper & S.R. Lele (Eds.), The nature of scientific evidence: Statistical, philosophical, and empirical considerations (pp. 17-50). Chicago: University of Chicago Press.
15. O'Hagan, A., & Forster, J. (2004). Kendall's advanced theory of statistics. Vol. 2B: Bayesian inference (2nd ed.). New York: Oxford University Press.
16. Rosenthal, R. (1994). Parametric measures of effect size. In H. Cooper & L.V. Hedges (Eds.), The handbook of research synthesis (pp. 231-244). New York: Russell Sage Foundation.
17. Rosnow, R.L., & Rosenthal, R. (2003). Effect sizes for experimenting psychologists. Canadian Journal of Experimental Psychology, 57, 221-237.
18. Royall, R. (1997). Statistical evidence: A likelihood paradigm. London: Chapman & Hall.
19. Scime, M., & Norvilitis, J.M. (2006). Task performance and response to frustration in children with Attention Deficit Hyperactivity Disorder. Psychology in the Schools, 43, 377-386.
20. Seidenfeld, T. (1979). Philosophical problems of statistical inference: Learning from R.A. Fisher. London: D. Reidel.
21. Thompson, B. (2002). What future quantitative social science research could look like: Confidence intervals for effect sizes. Educational Researchers. 31, 25-32.