Biostatistics and Epidemiology

PUBLISHED


Viewing: 1 - 10 of 231
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 
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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, 
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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 
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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 
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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 
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Paperback
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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Published:
April 28, 2014
Author(s):
Lisa Chasan-Taber
Competition for research funds in epidemiology, preventative medicine, and biostatistics has never been more intense and, at the same time, the grant application and review process at such agencies as the National Institutes of Health (NIH) is undergoing significant transformation. Writing 
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Published:
April 28, 2014
Author(s):
James E. De Muth
Building on its best-selling predecessors, Basic Statistics and Pharmaceutical Statistical Applications, Third Edition covers statistical topics most relevant to those in the pharmaceutical industry and pharmacy practice. It focuses on the fundamentals required to understand descriptive and 
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Published:
April 14, 2014
Editor(s):
Victoria Stodden, Friedrich Leisch, Roger D. Peng
In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must 
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Published:
April 04, 2014
Author(s):
Oscar Perpinan Lamigueiro
Code and Methods for Creating High-Quality Data Graphics A data graphic is not only a static image, but it also tells a story about the data. It activates cognitive processes that are able to detect patterns and discover information not readily available with the raw data. This is particularly 
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