TY  - BOOK
AU  - Hothorn, Torsten
TI  - Handbook of statistical analyses using R
SN  - 9781482204582
U1  - 519.50285 HOT 
PY  - 2014///
CY  - New York
PB  - CRC Press
KW  - Mathematical Statistics
KW  - Data processing handbook
KW  - R computer Program Language
KW  - R computer Programing Language
N1  - Alpha 1040/02 Jan 15
Rs.4023/-
; Table of Contents

Introduction 
Density Estimation 
Analysis Using R 
Summary of Findings 
Final Comments

Recursive Partitioning 
Introduction 
Recursive Partitioning 
Analysis Using R 
Summary of Findings
Final Comments 　　　

Scatterplot Smoothers and Additive Models 
Introduction 　　　
Scatterplot Smoothers and Generalised Additive Models 　　　
Analysis Using R 　　　
Summary of Findings
Final Comments

Survival Analysis 
Introduction 　　　
Survival Analysis 　　　
Analysis Using R 　　　
Summary of Findings
Final Comments 　　　

Quantile Regression
Introduction 　　　
Quantile Regression 　　　
Analysis Using R 　　　
Summary of Findings 　　　
Final Comments 　　　

Analysing Longitudinal Data I 
Introduction 　　　
Analysing Longitudinal Data 　　　
Linear Mixed Effects Models 　　　
Analysis Using R 　　　
Prediction of Random Effects 　　　
The Problem of Dropouts 　　　
Summary of Findings 　　　
Final Comments

Analysing Longitudinal Data II 
Introduction 　　　
Methods for Non-Normal Distributions 　　　
Analysis Using R: GEE 　　　
Analysis Using R: Random Effects 
Summary of Findings 　　　
Final Comments 　　　

Simultaneous Inference and Multiple Comparisons 
Introduction 　　　
Simultaneous Inference and Multiple Comparisons 　　　
Analysis Using R 　　　
Summary of Findings 　　　
Final Comments

Missing Values
Introduction 　　　
The Problems of Missing Data 　　　
Dealing with Missing Values 　　　
Imputing Missing Values 　　　
Analyzing Multiply Imputed Data 　　　
Analysis Using R 　　　
Summary of Findings 　　　
Final Comments

Meta-Analysis 
Introduction 　　　
Systematic Reviews and Meta-Analysis 　　　
Statistics of Meta-Analysis 　　　
Analysis Using R 　　　
Meta-Regression 　　　
Publication Bias 　　　
Summary of Findings 　　　
Final Comments 　　　

Bayesian Inference 
Introduction 　　　
Bayesian Inference 　　　
Analysis Using R 　　　
Summary of Findings 　　　
Final Comments 　　　

Principal Component Analysis 
Introduction 　　　
Principal Component Analysis 　　　
Analysis Using R 　　　
Summary of Findings 　　　
Final Comments

Multidimensional Scaling 
Introduction 　　　
Multidimensional Scaling 　　　
Analysis Using R 　　　
Summary of Findings 　　　
Final Comments 　　　

Cluster Analysis 
Introduction 　　　
Cluster Analysis 　　　
Analysis Using R 　　　
Summary of Findings 　　　
Final Comments

Bibliography

Index
N2  - Features

Presents straightforward descriptions of how to use R and interpret the results
Gives an introduction to R for novices, covering basic concepts and common data manipulation techniques
Shows how to obtain informative graphical output by applying the appropriate R functions
Includes more examples and exercises that encourage hands-on practice with R
Offers the data, R code, and lecture slides in the HSAUR3 package available from CRAN
Summary

Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis.

New to the Third Edition

Three new chapters on quantile regression, missing values, and Bayesian inference
Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables
Additional exercises
More detailed explanations of R code
New section in each chapter summarizing the results of the analyses
Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses
Whether you’re a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results
ER  -