社會科學研究方法一日千里，傳統上以線性模式來分析社會現象與教育現象的方式，受到不少質疑。近年來，社會科學界為了解決資料結構具有巢套與階層特性，常以階層線性模式（Hierarchical Linear and Nonlinear Models, HLM）或稱為多層次模型來分析，重點在於它更能掌握社會現象與教育現象的真實性，推論能更為準確，因而在企業管理、社會學與心理學運用的分析很多。 本書共分五篇
"This is a first-class book dealing with one of the most important areas of current research in applied statistics??Ythe methods described are widely applicable??Ythe standard of exposition is extr
This book provides a practical supplement to Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, coauthored by the first author, which will publish in a second edition in
"This book covers a wide range of statistical models, including hierarchical, hierarchical generalized linear, linear mixed, dynamic linear, smoothing, spatial, and longitudinal. It presents a framewo
Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.
Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.
This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretations that address scientific questions. A must-have for astronomers, its concrete approach will also be attractive to researchers in the sciences more generally.
Energy plays a vital role in economic and social development. The analysis of energy issues and policy options is therefore a vital area of study. This book presents a hierarchical modelling scheme intended to support energy planning and policy analysis in developing countries. The authors introduce the concept of 'Integrated National energy Planning' (INEP), and examine the spreadsheet models, optimization models, and linear planning models which energy planners use. Environmental considerations are also introduced into the analysis. Techniques are then applied to two important energy subsectors, electricity and fuelwood, before problems of integration and policy implementation are discussed. Throughout the book, the authors examine actual practice in developing countries. Illustrative case material is drawn from Egypt, West Africa, Sudan, Pakistan, Colombia, India, Sri Lanka and Morocco. This book will be of interest to students and practitioners of energy planning, and to those conc
This book/CD bundle of the greatly expanded third edition of Numerical Recipes now has wider coverage than ever before, many new, expanded and updated sections, and two completely new chapters. Co-authored by four leading scientists from academia and industry, Numerical Recipes starts with basic mathematics and computer science and proceeds to complete, working routines. The informal, easy-to-read style that made earlier editions so popular is kept throughout. Highlights of the new material include: a new chapter on classification and inference, Gaussian mixture models, HMMs, hierarchical clustering, and SVMs; a new chapter on computational geometry, covering KD trees, quad- and octrees, Delaunay triangulation, and algorithms for lines, polygons, triangles, and spheres; interior point methods for linear programming; MCMC; an expanded treatment of ODEs with completely new routines; and many new statistical distributions. For support or further licence information please visit www.nr.com
A comprehensive, self-contained survey of the theory and applications of differential games, one of the most commonly used tools for modelling and analysing economics and management problems which are characterised by both multiperiod and strategic decision making. Although no prior knowledge of game theory is required, a basic knowledge of linear algebra, ordinary differential equations, mathematical programming and probability theory is necessary. Part One presents the theory of differential games, starting with the basic concepts of game theory and going on to cover control theoretic models, Markovian equilibria with simultaneous play, differential games with hierarchical play, trigger strategy equilibria, differential games with special structures, and stochastic differential games. Part Two offers applications to capital accumulation games, industrial organization and oligopoly games, marketing, resources and environmental economics.
社會科學研究方法一日千里，傳統上以線性模式來分析社會現象與教育現象的方式，受到不少質疑。近年來，社會科學界為了解決資料結構具有巢套與階層特性，常以階層線性模式（Hierarchical Linear and Nonlinear Models, HLM）或稱為多層次模型來分析，重點在於它更能掌握社會現象與教育現象的真實性，推論能更為準確，因而在企業管理、社會學與心理學運用的分析很多。 本書共分五篇，包括：背景導論篇、學理基礎篇、實證設計篇、實證發現篇，以及結論應用篇，並由十二個章節所組成，各章均有體系描述說明。本書分析的實例是以台灣國二學生參與TIMSS 2007資料庫中的122所學校、2,549名學生的學習成就資料為分析依據；這份資料具有階層性，同時樣本取樣具有巢套特性，因此適合進行多層次模型的分析。本書的應用分析有益於國內對於學習成就與教育研究的長足進步，並拋開傳統資料處理分析方式，來掌握教育現況的真貌。
Energy plays a vital role in economic and social development. The analysis of energy issues and policy options is therefore a vital area of study. This book presents a hierarchical modelling scheme intended to support energy planning and policy analysis in developing countries. The authors introduce the concept of 'Integrated National energy Planning' (INEP), and examine the spreadsheet models, optimization models, and linear planning models which energy planners use. Environmental considerations are also introduced into the analysis. Techniques are then applied to two important energy subsectors, electricity and fuelwood, before problems of integration and policy implementation are discussed. Throughout the book, the authors examine actual practice in developing countries. Illustrative case material is drawn from Egypt, West Africa, Sudan, Pakistan, Colombia, India, Sri Lanka and Morocco. This book will be of interest to students and practitioners of energy planning, and to those conc
