Statistics

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Handbook of Quantile Regression

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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

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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

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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

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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

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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

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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...

Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition

Andrew B. Lawson
May 24, 2018

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in...

Graphics for Statistics and Data Analysis with R, Second Edition

Kevin J. Keen
May 18, 2018

Praise for the First Edition "The main strength of this book is that it provides a unified framework of graphical tools for data analysis, especially for univariate and low-dimensional multivariate data. In addition, it is clearly written in plain language and the inclusion of R code is...

Patterned Random Matrices

Arup Bose
May 17, 2018

Large dimensional random matrices (LDRM) with specific patterns arise in econometrics, computer science, mathematics, physics, and statistics. This book provides an easy initiation to LDRM. Through a unified approach, we investigate the existence and properties of the limiting spectral distribution...

Analytics and Knowledge Management

Suliman Hawamdeh, Hsia-Ching Chang
May 16, 2018

The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods,...

Nonparametric Models for Longitudinal Data: With Implementation in R

Colin O. Wu, Xin Tian
May 15, 2018

Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data. It covers methods, theories, and applications that are particularly useful for biomedical studies in the era...

Multivariate Kernel Smoothing and Its Applications

José E. Chacón, Tarn Duong
May 08, 2018

Kernel smoothing has greatly evolved since its inception to become an essential methodology in the Data Science tool kit for the 21st century. Its widespread adoption is due to its fundamental role for multivariate exploratory data analysis, as well as the crucial role it plays in composite...

R for Programmers: Quantitative Investment Applications

Dan Zhang
May 07, 2018

After the fundamental volume and the advanced technique volume, this volume focuses on R applications in the quantitative investment area. Quantitative investment has been hot for some years, and there are more and more startups working on it, combined with many other internet communities and...

Medical Statistics: An A-Z Companion, Second Edition

Filomena Pereira-Maxwell
May 04, 2018

This invaluable, jargon-free guide to essential medical terminology in an accessible A-Z format is ideal for medical, allied health and biomedical science students and researchers, clinicians and health care practitioners. Avoiding the complex language that is so often a feature of...

Multistate Models for the Analysis of Life History Data

Richard J Cook, Jerald F. Lawless
May 04, 2018

Multistate Models for the Analysis of Life History Data provides the first comprehensive treatment of multistate modeling and analysis, including parametric, nonparametric and semiparametric methods applicable to many types of life history data. Special models such as illness-death, competing risks...

Exploratory Data Analysis Using R

Ronald K. Pearson
May 04, 2018

Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to...

Handbook of Educational Measurement and Psychometrics Using R

Christopher D. Desjardins, Okan Bulut
May 02, 2018

Currently there are many introductory textbooks on educational measurement and psychometrics as well as R. However, there is no single book that covers important topics in measurement and psychometrics as well as their applications in R. The Handbook of Educational Measurement and Psychometrics...

Self-Controlled Case Series Studies: A Modelling Guide with R

Paddy Farrington, Heather Whitaker, Yonas Ghebremichael Weldeselassie
May 02, 2018

"The self-controlled case series has emerged as a key methodology for studying the effects of healthcare interventions. The overall literature around the self-controlled case series has exploded in recent years and this important and timely book pulls it all together in an effective and clear...

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