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For instance, the effect size may be an n-fold change of a gene tested under two conditions. Using clinical trials as an example, the sample size is the number of patients needed to conduct a clinical trial aimed at demonstrating a better treatment regimen relative to some standard of care or placebo vehicle. This number is calculated based on a fixed Type I error rate and a pre-specified power level to detect a pre-specified treatment effect size. Table 1 contains a glossary of terms often used in statistical inference and in the design of an experiment in sample size estimation.

Finally, it is important in these cases that the more traditional statistical approach with emphasis on model building followed by model-checking with residuals and outlier detection needs to be reconciled with the more algorithmic approach driven by prediction rates and functional minimization from the computer science community. 5. ACKNOWLEDGEMENTS I would like to thank the three anonymous referees for their careful reading of the manuscript and helpful suggestions. 6. REFERENCES Alizadeh AA, Eisen MB, Davis RE, Ma C, Losses IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X, Powell JI, Yang L, Martl GE, Moore T, Hudson J, Lu L, Lewis DB, Tibshirani R,Sherlock G, Chan WC, Greiner TC, Weisenburger DD, Armitage JO, Warnke R, Levy R, Wilson W, Grever MR, Byrd JC, Botstein D, Brown PO, Staudt LM.

1992, Gender and histologic type variations in smoking-related risk of lung cancer. Epidemiol. 3:61-64. , 1992, New aspects in the staging of lung cancer: prospective validation of the International Union Against Cancer TNM classification. Cancer 70:11021110. , 1991, Modeling tumor growth. Math Biosci. 103(1):97-114. , 2003, Gene expression profiles in human non-small and small cell lung cancers. Eur J Oncol. 39: 1936-1947. , 2001, Globocan 2000: Cancer Incidence, Mortality and Prevalence. Lyon, IARC Press.

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