Regression Methods in Biostatistics
โ Scribed by Eric Vittinghoff, David V. Glidden, Stephen C. Shiboski;Charles E. McCulloch
- Publisher
- Springer US
- Tongue
- English
- Category
- Library
No coin nor oath required. For personal study only.
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<P>This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for l
<P>This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for l
<p><P>This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models fo
This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for long
Maybe the title is redundant -- I'm not sure how many standard-bearer texts exist on robust biostatistics exist (Huber's general treatment of robust statistics, in its revised edition, is quite good, but it does not cover some of the practicalities involved in longitudinal studies or survival analys