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Probabilistic Causality In Longitudinal Studies
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Book Synopsis Probabilistic Causality in Longitudinal Studies by : Mervi Eerola
Download or read book Probabilistic Causality in Longitudinal Studies written by Mervi Eerola and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many applied fields of statistics the concept of causality is central to a scientific investigation. The author's aim in this book is to extend the classical theories of probabilistic causality to longitudinal settings and to propose that interesting causal questions can be related to causal effects which can change in time. The proposed prediction method in this study provides a framework to study the dynamics and the magnitudes of causal effects in a series of dependent events. Its usefulness is demonstrated by the analysis of two examples both drawn from biomedicine, one on bone marrow transplants and one on mental hospitalization. Consequently, statistical researchers and other scientists concerned with identifying causal relationships will find this an interesting and new approach to this problem.
Book Synopsis Latent Variable Modeling and Applications to Causality by : Maia Berkane
Download or read book Latent Variable Modeling and Applications to Causality written by Maia Berkane and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume gathers refereed papers presented at the 1994 UCLA conference on "La tent Variable Modeling and Application to Causality. " The meeting was organized by the UCLA Interdivisional Program in Statistics with the purpose of bringing together a group of people who have done recent advanced work in this field. The papers in this volume are representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Models and Causal Reasoning and the papers are innovations from contributors in disciplines not traditionally associated with behavioural sciences, (e. g. computer science with Judea Pearl and public health with James Robins). Also in this section are contri butions by Rod McDonald and Michael Sobel who have a more traditional approach to causal inference, generating from problems in behavioural sciences. The second section encompasses new approaches to questions of model selection with emphasis on factor analysis and time varying systems. Amemiya uses nonlinear factor analysis which has a higher order of complexity associated with the identifiability condi tions. Muthen studies longitudinal hierarchichal models with latent variables and treats the time vector as a variable rather than a level of hierarchy. Deleeuw extends exploratory factor analysis models by including time as a variable and allowing for discrete and ordi nal latent variables. Arminger looks at autoregressive structures and Bock treats factor analysis models for categorical data.
Book Synopsis A Probabilistic Theory of Causality by : Patrick Suppes
Download or read book A Probabilistic Theory of Causality written by Patrick Suppes and published by North-Holland. This book was released on 1970 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Analysing Change written by Ian Plewis and published by . This book was released on 1985 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the analysis of quantitative longitudinal data, emphasizing the difficult conceptual problems of measuring change with social science data. Aids in the construction of causal models using `real' longitudinal data from a broad range of contexts in the social sciences, including data relevant to educationalists, social and developmental psychologists, social administrators, sociologists, and political scientists.
Book Synopsis Probabilistic Causality and the Foundations of Modern Science by : Malcolm R. Forster
Download or read book Probabilistic Causality and the Foundations of Modern Science written by Malcolm R. Forster and published by . This book was released on 1984 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Unified Methods for Censored Longitudinal Data and Causality by : Mark J. van der Laan
Download or read book Unified Methods for Censored Longitudinal Data and Causality written by Mark J. van der Laan and published by Springer Science & Business Media. This book was released on 2012-11-12 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fundamental statistical framework for the analysis of complex longitudinal data is provided in this book. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures. The techniques go beyond standard statistical approaches and can be used to teach masters and Ph.D. students. The text is ideally suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data.
Book Synopsis Causality, Probability, and Time by : Samantha Kleinberg
Download or read book Causality, Probability, and Time written by Samantha Kleinberg and published by . This book was released on 2014-05-14 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents a new approach to causal inference and explanation, addressing both the timing and complexity of relationships. The method's feasibility and success is demonstrated through theoretical and experimental case studies"--
Book Synopsis Theories of Probabilistic Causality by : Phil Dowe
Download or read book Theories of Probabilistic Causality written by Phil Dowe and published by . This book was released on 1989 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Causality in Time Series: Challenges in Machine Learning by : Florin Popescu
Download or read book Causality in Time Series: Challenges in Machine Learning written by Florin Popescu and published by . This book was released on 2013-06 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume in the Challenges in Machine Learning series gathers papers from the Mini Symposium on Causality in Time Series, which was part of the Neural Information Processing Systems (NIPS) confernce in 2009 in Vancouver, Canada. These papers present state-of-the-art research in time-series causality to the machine learning community, unifying methodological interests in the various communities that require such inference.
Book Synopsis Causal Inference in Statistics by : Judea Pearl
Download or read book Causal Inference in Statistics written by Judea Pearl and published by John Wiley & Sons. This book was released on 2016-01-25 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.
Book Synopsis Linear Mixed Models in Practice by : Geert Verbeke
Download or read book Linear Mixed Models in Practice written by Geert Verbeke and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive treatment of linear mixed models, focusing on examples from designed experiments and longitudinal studies. Aimed at applied statisticians and biomedical researchers in industry, public health organisations, contract research organisations, and academia, this book is explanatory rather than mathematical rigorous. Although most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated, considerable effort was put into presenting the data analyses in a software-independent fashion.
Book Synopsis Proceedings of the First Seattle Symposium in Biostatistics: Survival Analysis by : Danyu Lin
Download or read book Proceedings of the First Seattle Symposium in Biostatistics: Survival Analysis written by Danyu Lin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: The papers in this volume discuss important methodological advances in several important areas, including multivariate failure time data and interval censored data. The book will be an indispensable reference for researchers and practitioners in biostatistics, medical research, and the health sciences.
Book Synopsis Case Studies in Environmental Statistics by : Douglas Nychka
Download or read book Case Studies in Environmental Statistics written by Douglas Nychka and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a set of case studies exemplifying the broad range of statis tical science used in environmental studies and application. The case studies can be used for graduate courses in environmental statistics, as a resource for courses in statistics using genuine examples to illustrate statistical methodol ogy and theory, and for courses in environmental science. Not only are these studies valuable for teaching about an essential cross-disciplinary activity but they can also be used to spur new research along directions exposed in these examples. The studies reported here resulted from a program of research carried on by the National Institute of Statistical Sciences (NISS) during the years 1992- 1996. NISS was created in 1991 as an initiative of the national statistics or ganizations, with the mission to renew and focus efforts of statistical science on important cross-disciplinary problems. One of NISS' first projects was a cooperative research effort with the U.S. Environmental Protection Agency (EPA) on problems of great interest to environmental science and regulation, surely one of today's most important cross-disciplinary activities. With the support and encouragement of Gary Foley, Director of the (then) U.S. EPA Atmospheric Research and Exposure Assessment Laboratory, a project and a research team were assembled by NISS that pursued a program which produced a set of results and products from which this book was drawn.
Book Synopsis Case Studies in Bayesian Statistics by : Constantine Gatsonis
Download or read book Case Studies in Bayesian Statistics written by Constantine Gatsonis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 4th Workshop on Case Studies in Bayesian Statistics was held at the Car negie Mellon University campus on September 27-28, 1997. As in the past, the workshop featured both invited and contributed case studies. The former were presented and discussed in detail while the latter were presented in poster format. This volume contains the four invited case studies with the accompanying discus sion as well as nine contributed papers selected by a refereeing process. While most of the case studies in the volume come from biomedical research the reader will also find studies in environmental science and marketing research. INVITED PAPERS In Modeling Customer Survey Data, Linda A. Clark, William S. Cleveland, Lorraine Denby, and Chuanhai LiD use hierarchical modeling with time series components in for customer value analysis (CVA) data from Lucent Technologies. The data were derived from surveys of customers of the company and its competi tors, designed to assess relative performance on a spectrum of issues including product and service quality and pricing. The model provides a full description of the CVA data, with random location and scale effects for survey respondents and longitudinal company effects for each attribute. In addition to assessing the performance of specific companies, the model allows the empirical exploration of the conceptual basis of consumer value analysis. The authors place special em phasis on graphical displays for this complex, multivariate set of data and include a wealth of such plots in the paper.
Book Synopsis Stochastic Epidemic Models and Their Statistical Analysis by : Hakan Andersson
Download or read book Stochastic Epidemic Models and Their Statistical Analysis written by Hakan Andersson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present lecture notes describe stochastic epidemic models and methods for their statistical analysis. Our aim is to present ideas for such models, and methods for their analysis; along the way we make practical use of several probabilistic and statistical techniques. This will be done without focusing on any specific disease, and instead rigorously analyzing rather simple models. The reader of these lecture notes could thus have a two-fold purpose in mind: to learn about epidemic models and their statistical analysis, and/or to learn and apply techniques in probability and statistics. The lecture notes require an early graduate level knowledge of probability and They introduce several techniques which might be new to students, but our statistics. intention is to present these keeping the technical level at a minlmum. Techniques that are explained and applied in the lecture notes are, for example: coupling, diffusion approximation, random graphs, likelihood theory for counting processes, martingales, the EM-algorithm and MCMC methods. The aim is to introduce and apply these techniques, thus hopefully motivating their further theoretical treatment. A few sections, mainly in Chapter 5, assume some knowledge of weak convergence; we hope that readers not familiar with this theory can understand the these parts at a heuristic level. The text is divided into two distinct but related parts: modelling and estimation.
Author :Harald Niederreiter Publisher :Springer Science & Business Media ISBN 13 :9780387983356 Total Pages :468 pages Book Rating :4.9/5 (833 download)
Book Synopsis Monte Carlo and Quasi-Monte Carlo Methods 1996 by : Harald Niederreiter
Download or read book Monte Carlo and Quasi-Monte Carlo Methods 1996 written by Harald Niederreiter and published by Springer Science & Business Media. This book was released on 1998 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods are numerical methods based on random sampling and quasi-Monte Carlo methods are their deterministic versions. This volume contains the refereed proceedings of the Second International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing which was held at the University of Salzburg (Austria) from July 9--12, 1996. The conference was a forum for recent progress in the theory and the applications of these methods. The topics covered in this volume range from theoretical issues in Monte Carlo and simulation methods, low-discrepancy point sets and sequences, lattice rules, and pseudorandom number generation to applications such as numerical integration, numerical linear algebra, integral equations, binary search, global optimization, computational physics, mathematical finance, and computer graphics. These proceedings will be of interest to graduate students and researchers in Monte Carlo and quasi-Monte Carlo methods, to numerical analysts, and to practitioners of simulation methods.
Author :Valerii V. Fedorov Publisher :Springer Science & Business Media ISBN 13 :9780387982151 Total Pages :136 pages Book Rating :4.9/5 (821 download)
Book Synopsis Model-Oriented Design of Experiments by : Valerii V. Fedorov
Download or read book Model-Oriented Design of Experiments written by Valerii V. Fedorov and published by Springer Science & Business Media. This book was released on 1997-06-20 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here, the authors explain the basic ideas so as to generate interest in modern problems of experimental design. The topics discussed include designs for inference based on nonlinear models, designs for models with random parameters and stochastic processes, designs for model discrimination and incorrectly specified (contaminated) models, as well as examples of designs in functional spaces. Since the authors avoid technical details, the book assumes only a moderate background in calculus, matrix algebra, and statistics. However, at many places, hints are given as to how readers may enhance and adopt the basic ideas for advanced problems or applications. This allows the book to be used for courses at different levels, as well as serving as a useful reference for graduate students and researchers in statistics and engineering.
