Kamis, 23 Mei 2013
Senin, 11 Maret 2013
Design of Observational Studies, Paul Rosenbaum
Design of Observational Studies PDF Download Ebook. Paul R. Rosenbaum offers complete introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies.
An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design.
This book is divided into four parts. Chapters 2, 3, and 5 of Part I cover concisely, in about one hundred pages, many of the ideas discussed in Rosenbaum’s Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates.
Part II includes a chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher’s striking advice for observational studies, "make your theories elaborate."
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Risk Analysis: A Quantitative Guide 3rd Edition, Vose
Risk Analysis: A Quantitative Guide 3rd Edition PDF Download Ebook. David Vose offers comprehensive guide for eh risk analyst and decision maker. Based on the author's extensive experience in solving real-world risk problems, this book is an invaluable aid to the risk analysis practitioner.
By providing the building blocks of risk-based thinking the author guides the reader through the steps necessary to produce a realistic risk-based thinking the author guides the reader through the steps necessary to produce a realistic risk analysis and offers general and specific techniques to cope with most common and challenging risk modeling problems. A wide range of solved examples is used to illustrate these technique and how they can be put together to make the best possible risk-based decisions.
This text has been thoroughly updated and expanded considerably with five new chapters for the risk manager, including how to plan and assess the quality of risk analysis, as well as new chapters for this risk analysis, as well as new chapters for the risk analysis modeller on summation of random variables, causality, optimization, insurance and finance modelling, forecasting, model validation and common errors, capital investment and microbial risk assessment.
This new edition provides a greater focus on business and includes applications in a wide range of different settings. It breaks down techniques into types of modelling issues (like distribution fitting, correlation and time series forecasting) and then applies them with easy-to-follow examples. Author explains powerful and proven Monte Carlo simulation and numerical techniques for dealing with uncertainty.
This text includes recent innovations in modelling like fast Fourier transforms and copulas with over 150 examples models and over 400 illustrations. Written in an informal manner with a practical rather than academic focus, this book discusses the planning, uses and abuses of risk analysis with compendium of almost eighty distribution types and their uses.
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Structured Analytic Techniques for Intelligence Analysis
Structured Analytic Techniques for Intelligence Analysis PDF Download Ebook. Richards J. Heuer Jr. and Randolph H. Pherson take the relatively new concept of structured analytic techniques, defines its place in a taxonomy of analytic methods, and moves it a giant leap forward. It describes 50 techniques that are divided into eight categories.
Each structured technique involves a step-by-step process that externalizes an individual analyst s thinking in a manner that makes it readily apparent to others, thereby enabling it to be shared, built on, and easily critiqued by others. This structured and transparent process combined with the intuitive input of subject matter experts is expected to reduce the risk of analytic error.
Our current high tech, global environment increasingly requires collaboration between analysts with different areas of expertise and analysts representing different organizational perspectives. Structured analytic techniques are the ideal process for guiding the interaction of analysts within a small team or group.
Each step in a technique prompts relevant discussion within the team, and such discussion generates and evaluates substantially more divergent information and more new ideas than a team that does not use a structured process.
By defining the domain of structured analytic techniques, providing a manual for using and teaching these techniques, and outlining procedures for evaluating and validating these techniques, this book lays a common ground for continuing improvement of how analysis is done.
These techniques are especially needed in the field of intelligence analysis where analysts typically deal with incomplete, ambiguous and sometimes deceptive information. However, these practical tools for analysis are also useful in a wide variety of professions including law enforcement, medicine, finance, and business.
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Kamis, 07 Maret 2013
New Introduction to Multiple Time Series Analysis
New Introduction to Multiple Time Series Analysis PDF Download Ebook. Helmut Lütkepohl provides a detailed introduction to the main steps of analyzing multiple time series, model specification, estimation, model checking, and for using the models for economic analysis and forecasting. The book now includes new chapters on cointegration analysis, structural vector autoregressions, cointegrated VARMA processes and multivariate ARCH models.
The book bridges the gap to the difficult technical literature on the topic. It is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it.
The book is oriented towards econometric applications; the text was prepared with economics and business students in mind, and examples and exercises are chosen accordingly. The text presents a collection of many of the topics currently treated in the literature. a ] this new version of a previous book by the author represents a timely addition to the time series and econometric literature. a ] The selection of topics responds to current trends in the literature.
Like its predecessor, this book provides the most complete coverage of stationary vector autoregressive (VAR) and vector autoregressive moving average (VARMA) models of any book. Incorporating more than six chapters of new material, this book also provides extensive coverage of the vector error-correction model (VECM) for cointegrated processes, structural VARs, structural VECMs, cointegrated VARMA processes, and multivariate models for conditionally heteroskedastic processes.
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A Companion to Theoretical Econometrics, Baltagi
A Companion to Theoretical Econometrics PDF Download Ebook. Badi H. Baltagi provides a comprehensive reference to the basics of econometrics. It focuses on the foundations of the field and at the same time integrates popular topics often encountered by practitioners.
The chapters are written by international experts and provide up-to-date research in areas not usually covered by standard econometric texts. This book is an exceptional reference for readers who require quick access to the foundation theories in this field. It focuses on the foundations of econometrics by integrating real-world topics encountered by professionals and practitioners.
This book draws on up-to-date research in areas not covered by standard econometrics texts, organized to provide clear, accessible information and point to further readings. Badi H. Baltagi is George Summey, Jr. Professor of Liberal Arts and Professor of Economics at Texas A & M University. He is a fellow and associate editor of the Journal of Econometrics, associate editor of Econometric Reviews, co-editor of Empirical Economics, and a recipient of the Multa Scripsit Award for Econometric Theory.
Chapters are organized to provide clear information and to point to further readings on the subject. Important topics covered include: serial correlation heteroskedasticity nonparametric and semiparametric models count and panel data regression models spatial correlation.
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Rabu, 06 Maret 2013
Econometric Methods with Applications in Business and Economics
Econometric Methods with Applications in Business and Economics PDF Download Ebook. Christiaan Heij, Paul de Boer, Philip Hans Franses and Teun Kloek describe econometric methods to support decision making. This book provides this, encouraging an active engagement with these methods by means of examples and exercises, so that the student develops a working understanding and hands-on experience with current day econometrics.
Taking a 'learning by doing' approach, it covers basic econometric methods (statistics, simple and multiple regression, nonlinear regression, maximum likelihood, and generalized method of moments), and addresses the creative process of model building with due attention to diagnostic testing and model improvement.
Its last part is devoted to two major application areas: the econometrics of choice data (logit and probit, multinomial and ordered choice, truncated and censored data, and duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussion of SUR models, panel data, and simultaneous equations).
Real-world text examples and practical exercise questions stimulate active learning and show how econometrics can solve practical questions in modern business and economic management. This book focuses on the core of econometrics, regression, and covers two major advanced topics, choice data with applications in marketing and micro-economics, and time series data with applications in finance and macro-economics.
Learning-support features include concise, manageable sections of text, frequent cross-references to related and background material, summaries, computational schemes, keyword lists, suggested further reading, exercise sets, and online data sets and solutions. Derivations and theory exercises are clearly marked for students in advanced courses.
This textbook is perfect for advanced undergraduate students, new graduate students, and applied researchers in econometrics, business, and economics, and for researchers in other fields that draw on modern applied econometrics.
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