Model Based Recursive Partitioning With Adjustment For Measurement Error

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Model-Based Recursive Partitioning with Adjustment for Measurement Error

Author : Hanna Birke
Publisher : Springer
ISBN 13 : 3658085053
Total Pages : 259 pages
Book Rating : 4.6/5 (58 download)

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Book Synopsis Model-Based Recursive Partitioning with Adjustment for Measurement Error by : Hanna Birke

Download or read book Model-Based Recursive Partitioning with Adjustment for Measurement Error written by Hanna Birke and published by Springer. This book was released on 2015-01-27 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning inspired recursive partitioning methods and regression models. Hanna Birke extends this approach by allowing in addition for measurement error in covariates, as frequently occurring in biometric (or econometric) studies, for instance, when measuring blood pressure or caloric intake per day. After an introduction into the background, the extended methodology is developed in detail for the Cox model and the Weibull model, carefully implemented in R, and investigated in a comprehensive simulation study.

Model-Based Recursive Partitioning with Adjustment for Measurement Error

Author : Hanna Birke
Publisher :
ISBN 13 : 9783658085063
Total Pages : pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Model-Based Recursive Partitioning with Adjustment for Measurement Error by : Hanna Birke

Download or read book Model-Based Recursive Partitioning with Adjustment for Measurement Error written by Hanna Birke and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning inspired recursive partitioning methods and regression models. Hanna Birke extends this approach by allowing in addition for measurement error in covariates, as frequently occurring in biometric (or econometric) studies, for instance, when measuring blood pressure or caloric intake per day. After an introduction into the background, the extended methodology is developed in detail for the Cox model and the Weibull model, carefully implemented in R, and investigated in a comprehensive simulation study. Contents MOB and Measurement Error Modelling Derivation of an Adjusted MOB Algorithm for Covariates Measured with Error for the Cox and Weibull Model Implementation of the Suggested Method for the Weibull Model in the Open-Source Programming Language R Simulation Study Showing the Performance of the Implemented Method Target Groups Researchers and students in the fields of statistics and cognate disciplines with interest in advanced modelling in combination with measurement error in covariates Data analysts of complex biometric or econometric studies with variables that are difficult to measure in practice The Author Hanna Birke wrote her master thesis under the supervision of Prof. Dr. Thomas Augustin at the department of statistics of the LMU Munich and is currently working on her doctoral thesis. .

Statistical Methods in Health Disparity Research

Author : J. Sunil Rao
Publisher : CRC Press
ISBN 13 : 1000905101
Total Pages : 341 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Statistical Methods in Health Disparity Research by : J. Sunil Rao

Download or read book Statistical Methods in Health Disparity Research written by J. Sunil Rao and published by CRC Press. This book was released on 2023-07-11 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: A health disparity refers to a higher burden of illness, injury, disability, or mortality experienced by one group relative to others attributable to multiple factors including socioeconomic status, environmental factors, insufficient access to health care, individual risk factors, and behaviors and inequalities in education. These disparities may be due to many factors including age, income, and race. Statistical Methods in Health Disparity Research will focus on their estimation, ranging from classical approaches including the quantification of a disparity, to more formal modeling, to modern approaches involving more flexible computational approaches. Features: Presents an overview of methods and applications of health disparity estimation First book to synthesize research in this field in a unified statistical framework Covers classical approaches, and builds to more modern computational techniques Includes many worked examples and case studies using real data Discusses available software for estimation The book is designed primarily for researchers and graduate students in biostatistics, data science, and computer science. It will also be useful to many quantitative modelers in genetics, biology, sociology, and epidemiology.

AMSTAT News

Author :
Publisher :
ISBN 13 :
Total Pages : 896 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis AMSTAT News by :

Download or read book AMSTAT News written by and published by . This book was released on 1996 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation

Author : Bruce B. Frey
Publisher : SAGE Publications
ISBN 13 : 1506326145
Total Pages : 1996 pages
Book Rating : 4.5/5 (63 download)

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Book Synopsis The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation by : Bruce B. Frey

Download or read book The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation written by Bruce B. Frey and published by SAGE Publications. This book was released on 2018-01-29 with total page 1996 pages. Available in PDF, EPUB and Kindle. Book excerpt: This encyclopedia is the first major reference guide for students new to the field, covering traditional areas while pointing the way to future developments.

GNSS – Global Navigation Satellite Systems

Author : Bernhard Hofmann-Wellenhof
Publisher : Springer Science & Business Media
ISBN 13 : 3211730176
Total Pages : 537 pages
Book Rating : 4.2/5 (117 download)

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Book Synopsis GNSS – Global Navigation Satellite Systems by : Bernhard Hofmann-Wellenhof

Download or read book GNSS – Global Navigation Satellite Systems written by Bernhard Hofmann-Wellenhof and published by Springer Science & Business Media. This book was released on 2007-11-20 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book extends the scientific bestseller "GPS - Theory and Practice" to cover Global Navigation Satellite Systems (GNSS) and includes the Russian GLONASS, the European system Galileo, and additional systems. The book refers to GNSS in the generic sense to describe the various existing reference systems for coordinates and time, the satellite orbits, the satellite signals, observables, mathematical models for positioning, data processing, and data transformation. This book is a university-level introductory textbook and is intended to serve as a reference for students as well as for professionals and scientists in the fields of geodesy, surveying engineering, navigation, and related disciplines.

Index Medicus

Author :
Publisher :
ISBN 13 :
Total Pages : 1844 pages
Book Rating : 4.:/5 (319 download)

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Book Synopsis Index Medicus by :

Download or read book Index Medicus written by and published by . This book was released on 2003 with total page 1844 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.

Modern Psychometrics with R

Author : Patrick Mair
Publisher : Springer
ISBN 13 : 3319931776
Total Pages : 464 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Modern Psychometrics with R by : Patrick Mair

Download or read book Modern Psychometrics with R written by Patrick Mair and published by Springer. This book was released on 2018-09-20 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook describes the broadening methodology spectrum of psychological measurement in order to meet the statistical needs of a modern psychologist. The way statistics is used, and maybe even perceived, in psychology has drastically changed over the last few years; computationally as well as methodologically. R has taken the field of psychology by storm, to the point that it can now safely be considered the lingua franca for statistical data analysis in psychology. The goal of this book is to give the reader a starting point when analyzing data using a particular method, including advanced versions, and to hopefully motivate him or her to delve deeper into additional literature on the method. Beginning with one of the oldest psychometric model formulations, the true score model, Mair devotes the early chapters to exploring confirmatory factor analysis, modern test theory, and a sequence of multivariate exploratory method. Subsequent chapters present special techniques useful for modern psychological applications including correlation networks, sophisticated parametric clustering techniques, longitudinal measurements on a single participant, and functional magnetic resonance imaging (fMRI) data. In addition to using real-life data sets to demonstrate each method, the book also reports each method in three parts-- first describing when and why to apply it, then how to compute the method in R, and finally how to present, visualize, and interpret the results. Requiring a basic knowledge of statistical methods and R software, but written in a casual tone, this text is ideal for graduate students in psychology. Relevant courses include methods of scaling, latent variable modeling, psychometrics for graduate students in Psychology, and multivariate methods in the social sciences.

Feature Engineering and Selection

Author : Max Kuhn
Publisher : CRC Press
ISBN 13 : 1351609467
Total Pages : 266 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Feature Engineering and Selection by : Max Kuhn

Download or read book Feature Engineering and Selection written by Max Kuhn and published by CRC Press. This book was released on 2019-07-25 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Scientific and Technical Aerospace Reports

Author :
Publisher :
ISBN 13 :
Total Pages : 1572 pages
Book Rating : 4.:/5 (31 download)

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Book Synopsis Scientific and Technical Aerospace Reports by :

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1992 with total page 1572 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Encyclopedia of Medical Decision Making

Author : Michael W. Kattan
Publisher : SAGE Publications
ISBN 13 : 1452261490
Total Pages : 1281 pages
Book Rating : 4.4/5 (522 download)

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Book Synopsis Encyclopedia of Medical Decision Making by : Michael W. Kattan

Download or read book Encyclopedia of Medical Decision Making written by Michael W. Kattan and published by SAGE Publications. This book was released on 2009-08-15 with total page 1281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision making is a critical element in the field of medicine that can lead to life-or-death outcomes, yet it is an element fraught with complex and conflicting variables, diagnostic and therapeutic uncertainties, patient preferences and values, and costs. Together, decisions made by physicians, patients, insurers, and policymakers determine the quality of health care, quality that depends inherently on counterbalancing risks and benefits and competing objectives such as maximizing life expectancy versus optimizing quality of life or quality of care versus economic realities. Broadly speaking, concepts in medical decision making (MDM) may be divided into two major categories: prescriptive and descriptive. Work in the area of prescriptive MDM investigates how medical decisions should be done using complicated analyses and algorithms to determine cost-effectiveness measures, prediction methods, and so on. In contrast, descriptive MDM studies how decisions actually are made involving human judgment, biases, social influences, patient factors, and so on. The Encyclopedia of Medical Decision Making gives a gentle introduction to both categories, revealing how medical and healthcare decisions are actually made—and constrained—and how physician, healthcare management, and patient decision making can be improved to optimize health outcomes. Key Features Discusses very general issues that span many aspects of MDM, including bioethics; health policy and economics; disaster simulation modeling; medical informatics; the psychology of decision making; shared and team medical decision making; social, moral, and religious factors; end-of-life decision making; assessing patient preference and patient adherence; and more Incorporates both quantity and quality of life in optimizing a medical decision Considers characteristics of the decisionmaker and how those characteristics influence their decisions Presents outcome measures to judge the quality or impact of a medical decision Examines some of the more commonly encountered biostatistical methods used in prescriptive decision making Provides utility assessment techniques that facilitate quantitative medical decision making Addresses the many different assumption perspectives the decision maker might choose from when trying to optimize a decision Offers mechanisms for defining MDM algorithms With comprehensive and authoritative coverage by experts in the fields of medicine, decision science and cognitive psychology, and healthcare management, this two-volume Encyclopedia is a must-have resource for any academic library.

Machine Learning and Data Science Blueprints for Finance

Author : Hariom Tatsat
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492073008
Total Pages : 432 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Machine Learning and Data Science Blueprints for Finance by : Hariom Tatsat

Download or read book Machine Learning and Data Science Blueprints for Finance written by Hariom Tatsat and published by "O'Reilly Media, Inc.". This book was released on 2020-10-01 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You’ll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations

Applied Predictive Modeling

Author : Max Kuhn
Publisher : Springer Science & Business Media
ISBN 13 : 1461468493
Total Pages : 595 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Applied Predictive Modeling by : Max Kuhn

Download or read book Applied Predictive Modeling written by Max Kuhn and published by Springer Science & Business Media. This book was released on 2013-05-17 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.

Computer Control in the Process Industries

Author : Brian Roffel
Publisher : CRC Press
ISBN 13 : 1351367404
Total Pages : 274 pages
Book Rating : 4.3/5 (513 download)

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Book Synopsis Computer Control in the Process Industries by : Brian Roffel

Download or read book Computer Control in the Process Industries written by Brian Roffel and published by CRC Press. This book was released on 2017-07-28 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Techniques such as dead time compensation, adaptive control and Kalman filtering have been around for some time, but as yet find little application in industry. This is due to several reasons, including: Articles in the literature usually assume that the reader is familiar with a specific topic and are therefore often difficult for the practicing control engineer to comprehend. Many practicing control engineers in the process industry have a chemical engineering background and did not receive a control engineering education. There is a wide gap between theory and practical implementation, since implementation is primarily concerned with robustness, and theory is not. The user therefore has to build an "expert shell" in order to achieve the desired robustness. Little is published on this issue, however. This book tries to promote the use of advanced control techniques by taking the reader from basic theory to practical implementation. It is therefore of interest to practicing control engineers in various types of industries, especially the process industry. Graduate and undergraduate students in control engineering will also find the book extremely useful since many practical details are given which are usually omitted in books on control engineering. Of special interest are the simulation examples, illustrating the application of various control techniques. The examples are available on a 5-1/4" floppy disk and can be used by anyone who has access to LOTUS 1-2-3. Chapter 1 is the introduction; Chapters 2 through 6 deal with distributed control system networks, computer system software, computer system selection, reliability and security, and batch and continuous control. Chapter 7 gives and introduction to advanced control. Chapters 8 through 11 deal with dead time compensation techniques and model identification. Chapters 12 through 14 discuss constraint control and design, and the adjustment and application of simple process models and optimization. Chapter 15 gives a thorough introduction to adaptive control, and the last two chapters deal with state and parameter estimation. This book is a valuable tool for everyone who realizes the importance of advanced control in achieving improved plant performance. It will take the reader from theory to practical implementation.

Modern Data Science with R

Author : Benjamin S. Baumer
Publisher : CRC Press
ISBN 13 : 0429575394
Total Pages : 830 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Modern Data Science with R by : Benjamin S. Baumer

Download or read book Modern Data Science with R written by Benjamin S. Baumer and published by CRC Press. This book was released on 2021-03-31 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

Continuous Time Modeling in the Behavioral and Related Sciences

Author : Kees van Montfort
Publisher : Springer
ISBN 13 : 3319772198
Total Pages : 446 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Continuous Time Modeling in the Behavioral and Related Sciences by : Kees van Montfort

Download or read book Continuous Time Modeling in the Behavioral and Related Sciences written by Kees van Montfort and published by Springer. This book was released on 2018-10-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book provides an overview of continuous time modeling in the behavioral and related sciences. It argues that the use of discrete time models for processes that are in fact evolving in continuous time produces problems that make their application in practice highly questionable. One main issue is the dependence of discrete time parameter estimates on the chosen time interval, which leads to incomparability of results across different observation intervals. Continuous time modeling by means of differential equations offers a powerful approach for studying dynamic phenomena, yet the use of this approach in the behavioral and related sciences such as psychology, sociology, economics and medicine, is still rare. This is unfortunate, because in these fields often only a few discrete time (sampled) observations are available for analysis (e.g., daily, weekly, yearly, etc.). However, as emphasized by Rex Bergstrom, the pioneer of continuous-time modeling in econometrics, neither human beings nor the economy cease to exist in between observations. In 16 chapters, the book addresses a vast range of topics in continuous time modeling, from approaches that closely mimic traditional linear discrete time models to highly nonlinear state space modeling techniques. Each chapter describes the type of research questions and data that the approach is most suitable for, provides detailed statistical explanations of the models, and includes one or more applied examples. To allow readers to implement the various techniques directly, accompanying computer code is made available online. The book is intended as a reference work for students and scientists working with longitudinal data who have a Master's- or early PhD-level knowledge of statistics.

Applying Quantitative Bias Analysis to Epidemiologic Data

Author : Timothy L. Lash
Publisher : Springer Science & Business Media
ISBN 13 : 0387879595
Total Pages : 200 pages
Book Rating : 4.3/5 (878 download)

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Book Synopsis Applying Quantitative Bias Analysis to Epidemiologic Data by : Timothy L. Lash

Download or read book Applying Quantitative Bias Analysis to Epidemiologic Data written by Timothy L. Lash and published by Springer Science & Business Media. This book was released on 2011-04-14 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bias analysis quantifies the influence of systematic error on an epidemiology study’s estimate of association. The fundamental methods of bias analysis in epi- miology have been well described for decades, yet are seldom applied in published presentations of epidemiologic research. More recent advances in bias analysis, such as probabilistic bias analysis, appear even more rarely. We suspect that there are both supply-side and demand-side explanations for the scarcity of bias analysis. On the demand side, journal reviewers and editors seldom request that authors address systematic error aside from listing them as limitations of their particular study. This listing is often accompanied by explanations for why the limitations should not pose much concern. On the supply side, methods for bias analysis receive little attention in most epidemiology curriculums, are often scattered throughout textbooks or absent from them altogether, and cannot be implemented easily using standard statistical computing software. Our objective in this text is to reduce these supply-side barriers, with the hope that demand for quantitative bias analysis will follow.