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

This greatly expanded third edition of Survival Analysis- A Self-learning Text provides a highly readable description of state-of-the-art methods of analysis of survival/event-history data. 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]. This is often reasonable, but sometimes it is not. An excellent introduction for all those coming to the subject for the first time. Survival Analysis: A Self-Learning Text, Third Edition (Statistics for Biology and Health). Applied longitudinal data analysis: Modeling change and event occurrence New York, USA: Oxford University Press. Aly C: Filtration rates of mosquito larvae in suspensions of latex microspheres and yeast cells. 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. Kniha Survival Analysis: A Self-Learning Text (David G. Buy Survival Analysis: A Self-Learning Text (Statistics for Biology and Health) Book Reviews. Logistic Regression: A Self-Learning Text (Statistics for Biology and Health) book download Download Logistic Regression: A Self-Learning Text (Statistics for Biology and Health) From the reviews of the third edition: “The third edition of this book continues the tradition of the authors of a two-column book that really does act as a self. Cancer: Survival Analysis: A Self-Learning Text (Statistics for Biology and Health). Survival Analysis – See Klein's page for data sets and errors. Survival Analysis: A Self-Learning Text – Data files here. Survival analysis: A self-learning text (2nd ed.). Kleinbaum DG, Klein M: Survival analysis: a self-learning text. Kleinbaum) - kúpte si ju pohodlne a za skvelú cenu hneď teraz na Martinus.sk. This FI network covers roughly each tissue in the series.