We briefly discuss the philosophical basis of science, causality, and scientific evidence, by introducing the hidden but most fundamental principle of science: the similarity principle. The principle’s use in scientific discovery is illustrated with Simpson’s paradox and other examples. In discussing the value of null hypothesis statistical testing, the controversies in multiple regression, and multiplicity issues in statistics, we describe how these difficult issues should be handled based on our interpretation of the similarity principle.
BenjaminiY.HochbergY. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B, 57, 289-300.
2.
ChangM. (2007). Adaptive design theory and implementation using SAS and R. Boca Raton, FL: CRC Press/Taylor Francis.
3.
ChangM. (2011). Modern issues and methods in biostatistics. New York, NY: Springer.
FisherR. A. (1973). Statistical methods and scientific inference (3rd ed.). London, England: Collins Macmillan.
7.
LehmannE. L. (1993). The Fisher, Neyman-Pearson theories of testing hypotheses: One theory or two?Journal of the American Statistical Association, 88, 1242-1249.
8.
LenchH. C.SaferM. A.LevineL. J. (2011). Focalism and the underestimation of future emotion: When it’s worse than imagined. Emotion, 11, 278-285.
9.
LordF. M. (1967). A paradox in the interpretation of group comparisons. Psychological Bulletin, 68, 304-305.
10.
SimpsonE. H. (1951). The interpretation of interaction in contingency tables. Journal of the Royal Statistical Society, Series B, 13, 238-241.
11.
SmullyanR. M. (1978). What is the name of this book? The riddle of Dracula and other logical puzzles. Englewood Cliffs, NJ: Prentice-Hall.
12.
TrafimowD. (2015). Introduction to the Special Issue on Mediation Analyses: What if planetary scientists used mediation analysis. Basic and Applied Social Psychology, 37, 197-201.
