# [Ebook] Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis (Springer Series in Statistics) By Jr. Frank E. Harrell – Tactical-player.co.uk

This Highly Anticipated Second Edition Features New Chapters And Sections, New References, And Comprehensive R Software In Keeping With The Previous Edition, This Book Is About The Art And Science Of Data Analysis And Predictive Modelling, Which Entails Choosing And Using Multiple Tools Instead Of Presenting Isolated Techniques, This Text Emphasises Problem Solving Strategies That Address The Many Issues Arising When Developing Multi Variable Models Using Real Data And Not Standard Textbook Examples Regression Modelling Strategies Presents Full Scale Case Studies Of Non Trivial Data Sets Instead Of Over Simplified Illustrations Of Each Method These Case Studies Use Freely Available R Functions That Make The Multiple Imputation, Model Building, Validation And Interpretation Tasks Described In The Book Relatively Easy To Do Most Of The Methods In This Text Apply To All Regression Models, But Special Emphasis Is Given To Multiple Regression Using Generalised Least Squares For Longitudinal Data, The Binary Logistic Model, Models For Ordinal Responses, Parametric Survival Regression Models And The Cox Semi Parametric Survival Model A New Emphasis Is Given To The Robust Analysis Of Continuous Dependent Variables Using Ordinal RegressionAs In The First Edition, This Text Is Intended For Masters Or PhD Level Graduate Students Who Have Had A General Introductory Probability And Statistics Course And Who Are Well Versed In Ordinary Multiple Regression And Intermediate Algebra The Book Will Also Serve As A Reference For Data Analysts And Statistical Methodologists, As It Contains An Up To Date Survey And Bibliography Of Modern Statistical Modelling Techniques

I purchased this book both for the study of data science and addressing a specific regression problem at work Unlike introductory textbooks, this book explains practicalities as to which tests or techniques are bett

Great

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

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

I bought this text after using and learning about Professor Harrell s contributions through the literature and through the R and S computing communities Others have written how wonderful Professor Harrell s software is to use, and how carefu

Great book Wish it had coverage of GLM analysis Gamma and Poisson regression Excellent and insightful R code.

My initial temptation is to say this is the best statistics text ever, but it s all relative It perfectly suits my current needs and state of development The book claims to be intended for graduate level students in biostatistics and I think that is a f

I found Regression Modeling Strategies to be a fantastic treatment of a wide assortment of model selection techniques Harrell s writing style is quite lucid assuming you ve had graduate level statistics coursework Model selection validation is arguably the mo

Informed, experienced update of this classical work on statistics, bringing to it additional years of Professor Frank Harrell, Jr s in depth experience, rules of thumb, and practicals.