Statistics

Per Page:
Sort:

Handbook of Quantile Regression

Featured

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

Featured

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

Featured

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

Featured

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

Featured

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, Third Edition: Techniques for Better Predictive Modeling and Analysis of Big Data, Third Edition

Featured

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...

Quantitative Techniques in Business, Management and Finance: A Case-Study Approach

Umeshkumar Dubey, D P Kothari, G K Awari
December 16, 2017

This book is especially relevant to undergraduates, postgraduates and researchers studying quantitative techniques as part of business, management and finance. It is an interdisciplinary book that covers all major topics involved at the interface between business and management on the one hand and...

Bayesian Inference for Stochastic Processes

Lyle D. Broemeling
December 15, 2017

This is the first book designed to introduce Bayesian inference procedures for stochastic processes. There are clear advantages to the Bayesian approach (including the optimal use of prior information). Initially, the book begins with a brief review of Bayesian inference and uses many examples...

Applied Surrogate Endpoint Evaluation Methods with SAS and R

Ariel Alonso, Theophile Bigirumurame, Tomasz Burzykowski, Marc Buyse, Geert Molenberghs, Leacky Muchene, Nolen Joy Perualila, Ziv Shkedy, Wim Van der Elst
December 13, 2017

An important factor that affects the duration, complexity and cost of a clinical trial is the endpoint used to study the treatment’s efficacy. When a true endpoint is difficult to use because of such factors as long follow-up times or prohibitive cost, it is sometimes possible to use a surrogate...

Big Data in Omics and Imaging: Association Analysis

Momiao Xiong
December 09, 2017

Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era. It is unique in that it presents both hypothesis testing and a data mining approach to holistically...

Process Capability Analysis: Estimating Quality

Neil W. Polhemus
December 07, 2017

Process Capability Analysis: Estimating Quality presents a systematic exploration of process capability analysis and how it may be used to estimate quality. The book is designed for practitioners who are tasked with insuring a high level of quality for the products and services offered by their...

Medical Biostatistics, Fourth Edition

Abhaya Indrayan, Rajeev Kumar Malhotra
December 06, 2017

Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Fourth Edition focuses on the statistical aspects ofmedicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties. This edition includes more topics in order to fill...

Spectral Feature Selection for Data Mining

Zheng Alan Zhao, Huan Liu
November 30, 2017

Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified...

Statistical Topics in Health Economics and Outcomes Research

Demissie Alemayehu, PhD, Joseph C. Cappelleri, PhD, Birol Emir, PhD, Kelly H. Zou, PhD, Pstat
November 28, 2017

With ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to...

Analyzing Health Data in R for SAS Users

Monika Maya Wahi, Peter Seebach
November 27, 2017

Analyzing Health Data in R for SAS Users is aimed at helping health data analysts who use SAS accomplish some of the same tasks in R. It is targeted to public health students and professionals who have a background in biostatistics and SAS software, but are new to R. For professors, it is useful...

Applied Biostatistical Principles and Concepts: Clinicians' Guide to Data Analysis and Interpretation

Laurens Holmes, Jr.
November 20, 2017

The past three decades have witnessed modern advances in statistical modeling and evidence discovery in biomedical, clinical, and population-based research. With these advances come the challenges in accurate model stipulation and application of models in scientific evidence discovery Applied...

Statistical Methods in Psychiatry and Related Fields: Longitudinal, Clustered, and Other Repeated Measures Data

Ralitza Gueorguieva
November 15, 2017

Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, there is natural heterogeneity in treatment responses and in other characteristics in the populations. Simple statistical...

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS

Kris Bogaerts, Arnost Komarek, Emmanuel Lesaffre
November 14, 2017

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years, interval...

Conferences

Year: