Title: Gaining Market Share for Nonparametric Statistics
1Gaining Market Share for Nonparametric Statistics
- Michael J. Schell
- Moffitt Cancer Center
- University of South Florida
2Web of Science
- Source of count data for this talk
- Words/phrases found in title or abstract
- Mainly title only references before 1991
- The number of articles has increased over the
years, thus the need for benchmarking
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4- But is the Market Itself Expanding?
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8- Non-Linear Regression Methods
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12Article Counts and Growth Rate of Regression
Sub-Fields
- Sub-Field 1990-94 2005-07 GR
- Non-linear 1469 2494 3.4
- Wavelets 1025 6114 11.9
- Linear 4360 8281 3.8
- Logistic 4291 16,728 7.8
- Mixed models 750 2817 7.5
- Data mining 11 2979 542
- Bioinformatics 14 4194 599
- Estimated 5-year rate obtained by doubling the
count - GR Growth Rate
13How Many Discoveries Have Been Lost by Ignoring
Modern Statistical Methods?Rand R. Wilcox,
American Psychologist, 1998
- Arbitrarily small departures from normality
result in low power even when distributions are
normal, heteroscedasticity can seriously lower
the power of standard ANOVA and regression
methods. - most quantitative articles tend to be too
technical for applied researchers. - If the goal is to avoid low power, the worst
method is the ANOVA F test. - the Theil-Sen estimator deserves consideration
as well.
14British Medical Journal articles by Doug Altman
- The scandal of poor medical research, 1994
- Why are errors so common? Put simply, much poor
research arise because researchers feel compelled
for career reasons to carry out research that
they are ill equipped to perform, and nobody
stops them. - Statistics and ethics in medical research. The
misuse of statistics is unethical, 1980
15Marketing of Pharmaceuticals
- Must have the produced the drug and shown its
efficacy - Need to produce the drug in mass quantities
- Marketing
16Marketing of Statistical Ideas
- Must have derived the statistic and demonstrated
its efficacy - Need to have available software
- Need to disseminate the idea
17Key Principle
- In an environment where ideas are not marketed,
first on the market wins
18First-on-the-market winners
- T-test, 1905
- ANOVA
- Kolmogorov-Smirnov test, 1937
- Duncans test, 1950
- Kaplan-Meier curves, 1958
- Cox regression, 1972
19Hodges and Lehmann , 19614th Berkeley Symposium
- Chernoff and Savage (1958) proved that the ARE of
the normal scores test is at least 1 - The above results suggest that on the basis of
power, at least for large samples, both the
Wilcoxon and normal scores tests are preferable
to the t-test for general use.
20First Simulation on Robustness of t-testCA
Boneau, 1960
- 320 citations
- Conclusion t-test is fine, exponential
distribution simulation was done wrong - Highest citation count on any subsequent
simulation study (39 thru 2000) 96
21Textbook Placement
- Basic Practice of Statistics, 4th Ed. 2006 David
S. Moore (728 pages) - Non-parametric tests dont make the book they
appear in the virtual appendix. - Statistics A Biomedical Introduction, 1977
- Hollander and Wolfe
- T-test in Chapter 5 Wilcoxon in Chapter 13
- Biostatistics, 2nd Ed. van Belle, Fisher, et al.,
2004 - T-test in Chapter 5 Wilcoxon in Chapter 8
22One-Way Layout for Books of Psalms
- Book N Mn SD Sk Kurt Range Md
- 1 41 15.0 9.3 1.9 4.6 5-50 12
- 2 31 15.0 8.0 1.1 0.9 5-36 12
- 3 17 21.1 16.7 2.3 5.4 7-72 18
- 4 17 18.9 13.2 1.2 0.5 5-48 15
- 5 44 15.9 26.1 5.6 34.5 2-43,176 9
- 150
23Results
- ANOVA p .7015
- ANOVA on logged data p .0586
- Kruskal-Wallis p .0458
- Normal scores p .0378
- AD sum for data 14 2.2 1.0 2.0
0.9 7.9 - AD sum for log data 1.9 0.3 0.3 0.5 0.2
0.6
24Deciding Between ANOVA and KW on Principle
- If one is convinced that the metric of the values
is what one wants, then ANOVA is fine - ANOVA political kin is the monarchy
- KW political kin is democracy
- Power assessed as P(X lt Y)
25Cancer Research
- It has been my experience as a statistician in
cancer research, that we are - rarely sure of the metric for the data,
- typically interested in answering the democratic
question - Thus, nonparametric analysis has predominated in
my applied articles
26Ethical Considerations
- Applied statistical work is very important in
decision-making - Educators have an ethical responsibility to
properly train their tool user students in best
practices - Tool user statisticians have an ethical
responsibility to seek best practice information