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Survival Analysis: A Self-Learning Text David G. Kleinbaum, Mitchel Klein
Publisher: Springer

York Press 2008-10-04 17:19 Lecture Notes in Survival Analysis (collection) by: Various Authors 2008-09-04 20:51 Survival Analysis: A Self-Learning Text (Statistics for Biology and Health) 2005-08 by: David G. New material has been added to the second edition and. The study also set out to analyze factors associated with the time until TST repetition at two HIV/AIDS referral services that carry out the TST on a routine basis in Recife, Pernambuco, Brazil. Survival analysis: a self-learning text. Survival Analysis: A Self-Learning Text (Statistics for Biology and Health). A prospective cohort study of 99 patients with 217 admissions with AECOPD. This FI network covers roughly each tissue in the series. Our method for discovering prognostic signatures builds on top of a human protein functional interaction (FI) network constructed by combining curated and uncurated data sources using a machine learning technique [24]. Applied longitudinal data analysis: Modeling change and event occurrence New York, USA: Oxford University Press. New York: Springer Science; 2005. Cancer: Survival Analysis: A Self-Learning Text (Statistics for Biology and Health). The probability of no TST repetition at the end of the follow-up period in patients whose initial test was nonreactive. Survival analysis: A self-learning text (2nd ed.). Product DescriptionAn excellent introduction for all those coming to the subject for the first time. We then apply this expression matrix for the superpc analysis [23] to search for linear combinations of network modules that are significantly correlated with patient survival or other clinically relevant criteria.