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Handbook of Quantile Regression


Roger Koenker, Victor Chernozhukov, Xuming He, Limin Peng
October 25, 2017

Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that mini...

Adaptive Survey Design


Barry Schouten, Andy Peytchev, James Wagner
August 4, 2017

Adaptive survey designs (ASDs) provide a framework for data-driven tailoring of data collection procedures to different sample members, often for cost and bias reduction. People vary in how likely they are to respond and in how they respond. This variation leads to opportunities to selectively deplo...

Methods in Comparative Effectiveness Research


Constantine Gatsonis, Sally C. Morton
February 7, 2017

Comparative effectiveness research (CER) is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care (IOM 2009). CER is conducted to develop evidence that will...

Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials


John O'Quigley, Alexia Iasonos, Björn Bornkamp
April 26, 2017

Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials gives a thorough presentation of state-of-the-art methods for early phase clinical trials. The methodology of clinical trials has advanced greatly over the last 20 years and, arguably, nowhere greater than that of ear...

Errors, Blunders, and Lies: How to Tell the Difference


David S. Salsburg
April 19, 2017

We live in a world that is not quite "right." The central tenet of statistical inquiry is that Observation = Truth + Error because even the most careful of scientific investigations have always been bedeviled by uncertainty. Our attempts to measure things are plagued with small errors. Our attempt...

Statistical and Machine-Learning Data Mining:: Techniques for Better Predictive Modeling and Analysis of Big Data, Third Edition


Bruce Ratner
June 1, 2017

The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. is a compilation of new and creative d...

Displaying Time Series, Spatial, and Space-Time Data with R

Oscar Perpinan Lamigueiro
August 14, 2018

Focusing on the exploration of data with visual methods, Displaying Time Series, Spatial, and Space-Time Data with R, Second Edition, presents methods and R code for producing high-quality static graphics, interactive visualizations, and animations of time series, spatial, and space-time data....

Encyclopedia of Biopharmaceutical Statistics - Four Volume Set

Shein-Chung Chow
August 13, 2018

Since the publication of the first edition in 2000, there has been an explosive growth of literature in biopharmaceutical research and development of new medicines. This encyclopedia (1) provides a comprehensive and unified presentation of designs and analyses used at different stages of the drug...

Handbook of Approximate Bayesian Computation

Scott A. Sisson, Yanan Fan, Mark Beaumont
August 10, 2018

As the world becomes increasingly complex, so do the statistical models required to analyse the challenging problems ahead. For the very first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and application of...

Modeling and Simulation Based Analysis in Reliability Engineering

Mangey Ram
August 10, 2018

Recent developments in reliability engineering has become the most challenging and demanding area of research. Modeling and Simulation, along with System Reliability Engineering has become a greater issue because of high-tech industrial processes using more complex systems today. This new book will...

Analytical Similarity Assessment in Biosimilar Product Development

Shein-Chung Chow
August 01, 2018

This book focuses on analytical similarity assessment in biosimilar product development following the FDA’s recommended stepwise approach for obtaining totality-of-the-evidence for approval of biosimilar products. It covers concepts such as the tiered approach for assessment of similarity of...

Compositional Data Analysis in Practice

Michael Greenacre
August 01, 2018

Compositional Data Analysis in Practice is a user-oriented practical guide to the analysis of data with the property of a constant sum, for example percentages adding up to 100%. Compositional data can give misleading results if regular statistical methods are applied, and are best analysed by...

Survey Sampling

Arijit Chaudhuri
July 24, 2018

This venture aspires to be a mix of a textbook at the undergraduate and postgraduate levels and a monograph to catch the attention of researchers in theoretical and practical aspects of survey sampling at diverse levels demanding a comprehensive review of what useful materials have preceded, with...

Technical Analysis of Stock Trends

Robert D. Edwards, John Magee, W.H.C. Bassetti
July 19, 2018

This revised and updated version of the best-selling book, Technical Analysis of Stock Trends, 10th Edition, presents proven long- and short-term stock trend analysis enabling investors to make smart, profitable trading decisions. The book covers technical theory such as The Dow Theory, reversal...

R Markdown: The Definitive Guide

Yihui Xie, J.J. Allaire, Garrett Grolemund
July 17, 2018

R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive...

Flexible Imputation of Missing Data, Second Edition

Stef van Buuren
July 16, 2018

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between...

Multiple Imputation in Practice: With Examples Using IVEware

Trivellore Raghunathan, Patricia A. Berglund, Peter W. Solenberger
July 12, 2018

Multiple Imputation in Practice: With Examples Using IVEware provides practical guidance on multiple imputation analysis, from simple to complex problems using real and simulated data sets. Data sets from cross-sectional, retrospective, prospective and longitudinal studies, randomized clinical...

Sparse Optimization Theory and Methods

Yun-Bin Zhao
July 09, 2018

Seeking sparse solutions of underdetermined linear systems is required in many areas of engineering and science such as signal and image processing. The efficient sparse representation becomes central in various big or high-dimensional data processing, yielding fruitful theoretical and realistic...