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Regression Analysis in Medical Research - for Starters and 2nd Levelers (Hardcover, 1st ed. 2018)
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Regression Analysis in Medical Research - for Starters and 2nd Levelers (Hardcover, 1st ed. 2018)
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This edition is a pretty complete textbook and tutorial for medical
and health care students, as well as a recollection/update bench,
and help desk for professionals. Novel approaches already applied
in published clinical research will be addressed: matrix analyses,
alpha spending, gate keeping, kriging, interval censored
regressions, causality regressions, canonical regressions,
quasi-likelihood regressions, novel non-parametric regressions.
Each chapter can be studied as a stand-alone, and covers one field
in the fast growing world of regression analyses. The authors, as
professors in statistics and machine learning at European
universities, are worried, that their students find
regression-analyses harder than any other methodology in
statistics. This is serious, because almost all of the novel
methodologies in current data mining and data analysis include
elements of regression-analysis. It is the main incentive for
writing this 28 chapter edition, consistent of - 28 major fields of
regression analysis, - their condensed maths, - their applications
in medical and health research as published so far, - step by step
analyses for self-assessment, - conclusion and reference sections.
Traditional regression analysis is adequate for epidemiology, but
lacks the precision required for clinical investigations. However,
in the past two decades modern regression methods have proven to be
much more precise. And so it is time, that a book described
regression analyses for clinicians. The current edition is the
first to do so. It is written for a non-mathematical readership.
Self-assessment data-files are provided through Springer' s "Extras
Online".
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