Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis (Springer Series in Statistics) Paperback – Illustrated, 22 Oct. 2016
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Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis (Springer Series in Statistics) Paperback – Illustrated, 22 Oct. 2016

4.5/5
Product ID: 202679345
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Reviews

4.5

All from verified purchases

A**R

Very Informative

I purchased this book both for the study of data science and addressing a specific regression problem at work. Unlike more introductory textbooks, this book explains more practicalities as to which tests or techniques are better suited for the situation. It helps to know better what to do when the data is not ideal.

D**O

Very good

Very well written and extensive review of regression model analysis. I would recommend.

S**S

Five Stars

Great

A**R

A challenging read for someone like me whose background in mathematics is thin and patchy

A challenging read for someone like me whose background in mathematics is thin and patchy. Even so I am learning a lot from it.

E**L

Great book

Tough read without some stats background but it’s a very well thought out book with actual examples and applications

V**Y

Best book on regression modeling

Frank Harrell's way of explaining methods along with R code is very useful, even for beginners.

F**S

Bibliografia OBRIGATÓRIA para estatísticos e cientistas de dados

Eu fiz uma graduação em estatística e quando eu fiz a disciplina de regressão, ou mesmo as disciplinas de projetos finais, ter lido esse livro teria feito toda a diferença. Esse livro aborda diversos fundamentos da modelagem que não são ensinados tradicionalmente em um curso de regressão. Alguns conhecimentos que impactaram bastante minha forma de trabalhar com modelagem foram:1 - como a discretização tem um impacto negativo na modelagem;2 - a importância de utilizar bootstrap em modelagem, avaliação de modelos e etc;3 - como não jogar informações fora com técnicas de modelagem ruins;4 - a importância de criar modelos interpretáveis ao invés de caixas-preta;e muito e muito mais. Esse deveria ser um livro de cabeceira para todo estatístico aplicado ou cientista de dados.Tem algum ponto ruim do livro? O autor é um bioestatístico e a maioria do exemplos são dessa área e com esse viés. Para mim não é de fato um problema mas pode ser algo relevante para alguns.

B**O

Un clásico del análisis de regresión

Un clásico en el análisis de la regresión. El autor desarrolla aquí su filosofía metodológica (a favor de la “regresión-regresión” en contraste con otras metodologías de “clasificación” y “black box” tan en boga en machine learning). Es muy pedagógico y apto para gente con distinta formación matemática

R**S

Very nice and useful

Very nice, extremely useful knowledge for people who want to understand regression modelling, easy to understand and has good examples. Hopefully there will be a newer version coming up.

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