Statistical significance tests are unnecessary even when properly done and properly interpreted: Reply to commentaries

International Journal of Forecasting

Volumn 23, Issue 2, 2007, Pages 335-336

  Armstrong, J Scott ^a  

^a NONE

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Indexed keywords

EID: 34249308889     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijforecast.2007.01.010     Document Type: Note

References (7)

1. Armstrong J.S. Principles of forecasting: A handbook for researchers and practitioners (2001), Kluwer, Boston
2. Becker B.J. Applying tests of combined significance in meta-analysis. Psychological Bulletin 102 (1987) 164-171
3. Gigerenzer G. Adaptive thinking: Rationality in the real world (2000), Oxford University Press, Oxford
4. Hunter J.E., and Schmidt F.L. Cumulative research knowledge and social policy formulation: The critical role of meta-analysis. Psychology, Public Policy, and Law 2 (1996) 324-347
5. Koning A.J., Franses P.H., Hibon M., and Stekler H.O. The M3 competition: Statistical tests of the results. International Journal of Forecasting 21 (2005) 397-409
6. Schmidt F.L. Statistical significance testing and cumulative knowledge in psychology: Implications for training of researchers. Psychological Methods 1 (1996) 115-129
7. Schmidt F.L., and Hunter J.E. Eight common but false objections to the discontinuation of significance testing in the analysis of research data. In: Harlow L.L., Mulaik S.A., and Steiger J.H. (Eds). What if there were no significance tests? (1997), Lawrence Erlbaum, London 37-64