Muutke küpsiste eelistusi

E-raamat: Survivorship Analysis for Clinical Studies

, (University of Liege, Belgium)
Teised raamatud teemal:
  • Formaat - EPUB+DRM
  • Hind: 279,50 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
  • Raamatukogudele
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

This unique reference/text provides an understanding of nonparametric and quasi­ parametric (regression) methods to analyze survivorship data in clinical studies­ emphasizing the interpretation and reasoning behind these methods.

Written for clinicians, as well as biostatisticians, Survivorship Analysis for Clinical Studies justifies each new methodology presented and clarifies its relationship to preceding material. It describes and explains established methods for summarizing the results of the majority of single-clinic survivorship studies, comparing two or more survival processes, and examining the effects of covariates on survival.

Including a diskette containing programs for computing confidence bands for survival curves, this book serves as a timely reference for biostatisticians, clinicians engaged in clinical trials, pharmacologists involved in new drug testing, epidemiologists, and biomedical engineers, and as a superb text for upper-level undergraduate and graduate students, as well as participants in professional seminars on survivorship data analysis in clinical settings.
Preface, 1 Estimation of Survival Probabilities 2 Standard Errors and Confidence Bands for Survival Rates and Curves 3 Nonparametric Methods for Comparison of Two or More Survival Curves 4 The Effects of Covariates on Survivorship: Proportional Hazards Models 5 Nonproportional Hazards 6 Survival Analysis with Time-Dependent Covariates 7 A Few Words on Computer Programs
Eugene K. Harris, University of Virginia, Charlottesville, Virginia. Adelin Albert, University of Liege, Belgium.