Biostatistics and Epidemiology

PUBLISHED


Viewing: 1 - 10 of 235
Published:
September 03, 2014
Author(s):
Helio S. Migon, Dani Gamerman, Francisco Louzada
A Balanced Treatment of Bayesian and Frequentist Inference Statistical Inference: An Integrated Approach, Second Edition presents an account of the Bayesian and frequentist approaches to statistical inference. Now with an additional author, this second edition places a more balanced emphasis on 
Published:
August 15, 2014
Author(s):
Geoff Der, Brian S. Everitt
Easily Use SAS to Produce Your Graphics Diagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they 
Published:
August 11, 2014
Author(s):
Christopher R. Bilder, Thomas M. Loughin
Learn How to Properly Analyze Categorical DataAnalysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses 
Published:
July 28, 2014
Author(s):
Sudipto Banerjee, Bradley P. Carlin, Alan E. Gelfand
Keep Up to Date with the Evolving Landscape of Space and Space-Time Data Analysis and Modeling Since the publication of the first edition, the statistical landscape has substantially changed for analyzing space and space-time data. More than twice the size of its predecessor, Hierarchical Modeling 
Published:
July 17, 2014
Author(s):
Brady T. West, Kathleen B. Welch, Andrzej T Galecki
Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues 
Published:
July 17, 2014
Author(s):
Ken Kleinman, Nicholas J. Horton
An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, 
Published:
July 14, 2014
Author(s):
Marc Lavielle
Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects ModelsMixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools presents a rigorous framework for describing, implementing, and using mixed effects models. With these models, readers can 
Published:
July 01, 2014
Author(s):
Julian J. Faraway
A Hands-On Way to Learning Data Analysis Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with 
Published:
June 25, 2014
Author(s):
Torsten Hothorn, Brian S. Everitt
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 
Published:
June 06, 2014
Author(s):
Sadanori Konishi
Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling shows how multivariate analysis is widely used for extracting useful information and patterns from multivariate data and for understanding the structure of random 

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