Download or read book Data Matching written by Peter Christen and published by Springer Science & Business Media. This book was released on 2012-07-04 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases. Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today. By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.
Download or read book The Matching Methodology Some Statistical Properties written by Prem K. Goel and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Incomplete-data problems arise naturally in many instances of statistical practice. One class of incomplete-data problems, which is relatively not well understood by statisticians, is that of merging micro-data files. Many Federal agencies use the methodology of file-merging to create comprehensive files from multiple but incomplete sources of data. The main objective of this endeavor is to perform statistical analyses on the synthetic data set generated by file merging. In general, these analyses cannot be performed by analyzing the incomplete data sets separately. The validity and the efficacy of the file-merging methodology can be assessed by means of statistical models underlying the mechanisms which may generate the incomplete files. However, a completely satisfactory and unified theory of file-merging has not yet been developed This monograph is only a minor attempt to fill this void for unifying known models. Here, we review the optimal properties of some known matching strategies and derive new results thereof. However, a great number of unsolved problems still need the attention of very many researchers. One main problem still to be resolved is the development of appropriate inference methodology from merged files if one insists on using file merging methodology. If this monograph succeeds in attracting just a few more mathematical statisticians to work on this class of problems, then we will feel that our efforts have been successful.
Download or read book Template Matching Techniques in Computer Vision written by Roberto Brunelli and published by John Wiley & Sons. This book was released on 2009-04-29 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli: examines the basics of digital image formation, highlighting points critical to the task of template matching; presents basic and advanced template matching techniques, targeting grey-level images, shapes and point sets; discusses recent pattern classification paradigms from a template matching perspective; illustrates the development of a real face recognition system; explores the use of advanced computer graphics techniques in the development of computer vision algorithms. Template Matching Techniques in Computer Vision is primarily aimed at practitioners working on the development of systems for effective object recognition such as biometrics, robot navigation, multimedia retrieval and landmark detection. It is also of interest to graduate students undertaking studies in these areas.
Download or read book The Matching Methodology written by Prem K Goel and published by . This book was released on 1989-05-01 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Assessment of Matching Methods for Casual Analysis written by Uche Okoro and published by . This book was released on 2019 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Author's abstract: Abstract Introduction: Matching could be defined as “any method that aims to equate (or “balance”) the distribution of covariates in the treated and control groups”. It could entail 1:1 matching, weighting or sub classification (Stuart, 2010). Objectives: The objectives of this study are: (1) To compare several matching methods with the aim of choosing the best method for matching groups in causal analysis. (2) To apply the results of the study to real world data to estimate causal effect. Methods: For this study a dataset S was simulated which is representative of data on hypertensive patients enrolled in a randomized, double blind, placebo (P) controlled clinical trial of a dose of a drug D. The effect measure of interest is the mean difference. Matchit was used for the simulations study. Matchit works in conjunction with the R programming language statistical software. Results: Looking at the different matching methods side by side from both the one sample simulation and the simulation with 500 different samples, the Genetic Matching method appeared to be the best matching method as it is the matching method that produces dataset that satisfied all the conditions for normality as specified by the normality plots of the histogram, the Shapiro-Wilks’s test and the quantile-quantile plots. Conclusion: The study showed that the Genetic Matching Method was better than the Nearest Neighbor, Optimal, Coarsened Exact and the Mahalanobis Matching Methods
Download or read book The Evaluation of the Matching Method written by Philip Ewart Vernon and published by . This book was released on 1936 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Matching written by Marcello D'Orazio and published by John Wiley & Sons. This book was released on 2006-03-30 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is more statistical data produced in today’s modern society than ever before. This data is analysed and cross-referenced for innumerable reasons. However, many data sets have no shared element and are harder to combine and therefore obtain any meaningful inference from. Statistical matching allows just that; it is the art of combining information from different sources (particularly sample surveys) that contain no common unit. In response to modern influxes of data, it is an area of rapidly growing interest and complexity. Statistical Matching: Theory and Practice introduces the basics of statistical matching, before going on to offer a detailed, up-to-date overview of the methods used and an examination of their practical applications. Presents a unified framework for both theoretical and practical aspects of statistical matching. Provides a detailed description covering all the steps needed to perform statistical matching. Contains a critical overview of the available statistical matching methods. Discusses all the major issues in detail, such as the Conditional Independence Assumption and the assessment of uncertainty. Includes numerous examples and applications, enabling the reader to apply the methods in their own work. Features an appendix detailing algorithms written in the R language. Statistical Matching: Theory and Practice presents a comprehensive exploration of an increasingly important area. Ideal for researchers in national statistics institutes and applied statisticians, it will also prove to be an invaluable text for scientists and researchers from all disciplines engaged in the multivariate analysis of data collected from different sources.
Download or read book Matching by the Propensity Score Methodology with Applications in R written by Christian Ibarra (Graduate student) and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A theoretical framework will be presented for each matching algorithm, and cross-sectional, time-to-event, and multinomial data sets will be analyzed. We will explore the performance of the techniques through graphical and regression comparisons of pre-matched and post-matched data sets, comparing how balanced the data sets are with respect to matching (confounding) variables. The analysis will be done in R 4.2.1 software. The codes will utilize a built-in package called “MatchIt” along with other advanced packages, such as “Twang.”
Download or read book Propensity Score Analysis written by Shenyang Guo and published by SAGE. This book was released on 2015 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides readers with a systematic review of the origins, history, and statistical foundations of Propensity Score Analysis (PSA) and illustrates how it can be used for solving evaluation and causal-inference problems.
Download or read book Matching Methods in Practice written by Guido W. Imbens and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a large theoretical literature on methods for estimating causal effects under unconfoundedness, exogeneity, or selection--on--observables type assumptions using matching or propensity score methods. Much of this literature is highly technical and has not made inroads into empirical practice where many researchers continue to use simple methods such as ordinary least squares regression even in settings where those methods do not have attractive properties. In this paper I discuss some of the lessons for practice from the theoretical literature, and provide detailed recommendations on what to do. I illustrate the recommendations with three detailed applications.
Download or read book Relational Matching written by George Vosselman and published by Springer Science & Business Media. This book was released on 1992-09-10 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an introduction to recursive functions intended for graduate students. It presupposes some mathematical maturity and a slight aquaintancewith some important topics, such as group theory and topology. Some acquaintance with logic is desirable but not essential. It introduces the main topics of recusion theory, such as hierarchy theory, RE sets, and undecidable theories, without going very deeply into any of them.
Download or read book Matching Methods in Practice written by Guido M. Imbens and published by . This book was released on 2014 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a large theoretical literature on methods for estimating causal effects under unconfoundedness, exogeneity, or selection--on--observables type assumptions using matching or propensity score methods. Much of this literature is highly technical and has not made inroads into empirical practice where many researchers continue to use simple methods such as ordinary least squares regression even in settings where those methods do not have attractive properties. In this paper I discuss some of the lessons for practice from the theoretical literature, and provide detailed recommendations on what to do. I illustrate the recommendations with three detailed applications.
Download or read book Data Driven Policy Impact Evaluation written by Nuno Crato and published by Springer. This book was released on 2018-10-02 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the light of better and more detailed administrative databases, this open access book provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation.
Download or read book Aortopathy written by Koichiro Niwa and published by Springer. This book was released on 2017-02-09 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook to focus on Aortopathy, a new clinical concept for a form of vasculopathy. The first section of the book starts from discussing general concept and history of Aortopathy, and then deals with its pathophysiology, manifestation, intrinsic factor, clinical implication, management and prevention. The second part closely looks at various disorders of the Aortopathy such as bicuspid aortic valve and coarctation of aorta. The book editors have published a lot of works on the topic and have been collecting relating data in the field of congenital heart disease for the past 20 years, thus present the book with confidence. The topic - an association of aortic pathophysiological abnormality, aortic dilation and aorto-left ventricular interaction - is getting more and more attention among cardiovascular physicians. This is the first book to refer for cardiologists, pediatric cardiologists, surgeons, ACHD specialists, etc. to acquire thorough knowledge on Aortopathy.
Download or read book Algorithmics of Matching Under Preferences written by David F. Manlove and published by World Scientific. This book was released on 2013 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Matching problems with preferences are all around us OCo they arise when agents seek to be allocated to one another on the basis of ranked preferences over potential outcomes. Efficient algorithms are needed for producing matchings that optimise the satisfaction of the agents according to their preference lists.In recent years there has been a sharp increase in the study of algorithmic aspects of matching problems with preferences, partly reflecting the growing number of applications of these problems worldwide. This book describes the most important results in this area, providing a timely update to The Stable Marriage Problem: Structure and Algorithms (D Gusfield and R W Irving, MIT Press, 1989) in connection with stable matching problems, whilst also broadening the scope to include matching problems with preferences under a range of alternative optimality criteria."
Download or read book Propensity Score Analysis written by Wei Pan and published by Guilford Publications. This book was released on 2015-04-07 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to help researchers better design and analyze observational data from quasi-experimental studies and improve the validity of research on causal claims. It provides clear guidance on the use of different propensity score analysis (PSA) methods, from the fundamentals to complex, cutting-edge techniques. Experts in the field introduce underlying concepts and current issues and review relevant software programs for PSA. The book addresses the steps in propensity score estimation, including the use of generalized boosted models, how to identify which matching methods work best with specific types of data, and the evaluation of balance results on key background covariates after matching. Also covered are applications of PSA with complex data, working with missing data, controlling for unobserved confounding, and the extension of PSA to prognostic score analysis for causal inference. User-friendly features include statistical program codes and application examples. Data and software code for the examples are available at the companion website (www.guilford.com/pan-materials).
Download or read book A Comparison of Propensity Score Matching Methods in R with the Matchit Package written by Jiaqi Zhang and published by . This book was released on 2013 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Propensity score matching (PSM) methods are becoming increasingly popular in non-experimental and observational studies to reduce selection bias through balancing measured covariates. This process has been developed into a relatively systematic and scientific branch of matching methods. MatchIt is a package in the statistical programming software R that allows for matching using several methods, including nearest neighbor, caliper, stratification, and full matching in order to find cases balanced on the propensity score between the treatment and the control group and achieve causal inference. Choosing which of those options to implement can be confusing for researchers. In this present study, these different methods are explained and a simulation study is conducted using example data to illustrate differences in these methods. The generated data is assigned based on a function of observed covariates and randomness, simulating selection bias, and analyzed to examine whether any of five popular propensity score matching methods perform more effectively in balancing covariates and reducing the selection bias within a given sample size. This study shows that each propensity score matching method -- Nearest Neighbor (1:1), Nearest Neighbor (2:1), Caliper, Stratification, and Full matching methods -- performs well in matching, and they all provide strong evidence to make casual inferences. This is particularly true for Caliper and Full matching. R code, detailed results and suggestions for future study are also provided.
