Use of Bootstrapping to Evaluate Infrequent Genetic Abnormalities as Prognostic Factors for Survival in Human Acute Leukemias

David D. Lawrence, Peter A. Reese and Clara D. Bloomfield
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David D. Lawrence: Roswell Park Cancer Institute, New York State Department of Health, Department of Medicine
Peter A. Reese: Roswell Park Cancer Institute, New York State Department of Health, Department of Biomathematics
Clara D. Bloomfield: Roswell Park Cancer Institute, New York State Department of Health, Department of Medicine

A chapter in Computing Science and Statistics, 1992, pp 425-429 from Springer

Abstract: Abstract The distributional properties of a summary random variable in a two-sample test involving a small group can be investigated through bootstrapping. With data from a prospective Cancer and Leukemia Group B (CALGB 8461) study of the prognostic significance of cytogenetic abnormalities on human acute leukemias, survival data involving an infrequent genetic abnormality was bootstrapped using Cox’s proportional hazards regression model. Eight of 578 cases in the survival analysis exhibited trisomy 13 as the sole cytogenetic abnormality. Although the bootstrap results agree with the classical log-rank test, the distribution of bootstrap regression coefficients deviates from normality (P

Keywords: Score Function; Bootstrap Sample; Partial Likelihood; Regression Coefficient Estimate; Bootstrap Distribution (search for similar items in EconPapers)
Date: 1992
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DOI: 10.1007/978-1-4612-2856-1_68

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