The asymmetry of predictive and descriptive capabilities in quantitative communication research: Implications for hypothesis development and testing

Communication Methods and Measures

Volumn 5, Issue 2, 2011, Pages 113-125

  O'Keefe, Daniel J ^a  

^a NORTHWESTERN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79959237530     PISSN: 19312458     EISSN: 19312466     Source Type: Journal    
DOI: 10.1080/19312458.2011.568375     Document Type: Article

References (19)

1. Cohen, J. (1990). Things I have learned (so far). American Psychologist, 45, 1304-1312.
2. Cortina, J. M., & Dunlap, W. P. (1997). On the logic and purpose of significance testing. Psychological Methods, 2, 161-172.
3. Fidler, F., & Loftus, G. R. (2009). Why figures with error bars should replace p values: Some conceptual arguments and empirical demonstrations. Zeitschrift Fur Psychologie, 217, 27-37.
4. Fidler, F., Thomason, N., Cumming, G., Finch, S., & Leeman, J. (2004). Editors can lead researchers to confidence intervals, but can't make them think: Statistical reform lessons from medicine. Psychological Science, 15, 119-126.
5. Frick, R.W. (1998). Interpreting statistical testing: Process and propensity, not population and random sampling. Behavior Research Methods, Instruments, and Computers, 30, 527-535.
6. Harlow, L. L., Mulaik, S. A., & Steiger, J. H. (Eds.). (1997). What if there were no significance tests? Mahwah, NJ: Erlbaum.
7. Harris, R. J. (1997a). Reforming significance testing via three-valued logic. In L. L. Harlow, S. A. Mulaik, & J. H. Steiger (Eds.), What if there were no significance tests? (pp. 145-174). Mahwah, NJ: Erlbaum.
8. Harris, R. J. (1997b). Significance tests have their place. Psychological Science, 8, 8-11.
9. Hullett, C. R. (2007). Concerns about error go beyond cumulating Type I error: A response to Matsunaga. Communication Methods and Measures, 1, 275-279.
10. Jackson, S. (1992). Message effects research: Principles of design and analysis. New York, NY: Guilford Press.
11. Jones, L. V., & Tukey, J. W. (2000). A sensible formulation of the significance test. Psychological Methods, 5, 411-414.
12. Konold, C., & Pollatsek, A. (2002). Data analysis as the search for signals in noisy processes. Journal for Research in Mathematics Education, 33, 259-289.
13. Levine, T. R., Weber, R., Hullett, C., Park, H. S., & Lindsey, L. L. (2008). A critical assessment of null hypothesis significance testing in quantitative communication research. Human Communication Research, 34, 171-187.
14. Levine, T. R., Weber, R., Park, H. S., & Hullett, C. (2008). A communication researchers' guide to null hypothesis significance testing and alternatives. Human Communication Research, 34, 188-209.
15. Loftus, G. R. (1996). Psychology will be a much better science when we change the way we analyze data. Current Directions in Psychological Science, 5, 161-171.
16. Natrella, M. G. (1960). The relation between confidence intervals and tests of significance. American Statistician, 14(1), 20-22, 38.
17. Schmidt, F. L. (1996). Statistical significance testing and cumulative knowledge in psychology: Implications for training of researchers. Psychological Methods, 1, 115-129.
18. Tukey, J. W. (1991). The philosophy of multiple comparisons. Statistical Science, 6, 100-116.
19. Wellek, S. (2002). Testing statistical hypotheses of equivalence. Boca Raton, FL: Chapman & Hall/CRC.