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Author: Anthony S. Bryk Publisher: SAGE Publications, Incorporated ISBN: Category : Social Science Languages : en Pages : 296
Book Description
Hierarchical Linear Models launches a new Sage series, Advanced Quantitative Techniques in the Social Sciences. This introductory text explicates the theory and use of hierarchical linear models (HLM) through rich, illustrative examples and lucid explanations. The presentation remains reasonably nontechnical by focusing on three general research purposes - improved estimation of effects within an individual unit, estimating and testing hypotheses about cross-level effects, and partitioning of variance and covariance components among levels. This innovative volume describes use of both two and three level models in organizational research, studies of individual development and meta-analysis applications, and concludes with a formal derivation of the statistical methods used in the book.
Author: Anthony S. Bryk Publisher: SAGE Publications, Incorporated ISBN: Category : Social Science Languages : en Pages : 296
Book Description
Hierarchical Linear Models launches a new Sage series, Advanced Quantitative Techniques in the Social Sciences. This introductory text explicates the theory and use of hierarchical linear models (HLM) through rich, illustrative examples and lucid explanations. The presentation remains reasonably nontechnical by focusing on three general research purposes - improved estimation of effects within an individual unit, estimating and testing hypotheses about cross-level effects, and partitioning of variance and covariance components among levels. This innovative volume describes use of both two and three level models in organizational research, studies of individual development and meta-analysis applications, and concludes with a formal derivation of the statistical methods used in the book.
Author: V. Kulish Publisher: Springer Science & Business Media ISBN: 0306480611 Category : Science Languages : en Pages : 360
Book Description
Everybody is current in a world surrounded by computer. Computers determine our professional activity and penetrate increasingly deeper into our everyday life. Therein we also need increasingly refined c- puter technology. Sometimes we think that the next generation of c- puter will satisfy all our dreams, giving us hope that most of our urgent problems will be solved very soon. However, the future comes and il- sions dissipate. This phenomenon occurs and vanishes sporadically, and, possibly, is a fundamental law of our life. Experience shows that indeed ‘systematically remaining’ problems are mainly of a complex tech- logical nature (the creation of new generation of especially perfect - croschemes, elements of memory, etc. ). But let us note that amongst these problems there are always ones solved by our purely intellectual efforts alone. Progress in this direction does not require the invention of any ‘superchip’ or other similar elements. It is important to note that the results obtained in this way very often turn out to be more significant than the ‘fruits’ of relevant technological progress. The hierarchical asymptotic analytical–numerical methods can be - garded as results of such ‘purely intellectual efforts’. Their application allows us to simplify essentially computer calculational procedures and, consequently, to reduce the calculational time required. It is obvious that this circumstance is very attractive to any computer user.
Author: Stephen W. Raudenbush Publisher: SAGE ISBN: 9780761919049 Category : Social Science Languages : en Pages : 520
Book Description
New edition of a text in which Raudenbush (U. of Michigan) and Bryk (sociology, U. of Chicago) provide examples, explanations, and illustrations of the theory and use of hierarchical linear models (HLM). New material in Part I (Logic) includes information on multivariate growth models and other topics.
Author: Gregory R. Hancock Publisher: Routledge ISBN: 1135172994 Category : Education Languages : en Pages : 449
Book Description
Designed for reviewers of research manuscripts and proposals in the social and behavioral sciences, and beyond, this title includes chapters that address traditional and emerging quantitative methods of data analysis.
Author: J. Andrew Royle Publisher: Elsevier ISBN: 0080559255 Category : Science Languages : en Pages : 464
Book Description
A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics * Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) * Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis * Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS * Computing support in technical appendices in an online companion web site
Author: Rob J Hyndman Publisher: OTexts ISBN: 0987507117 Category : Business & Economics Languages : en Pages : 380
Book Description
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Author: Fabian Klopfer Publisher: GRIN Verlag ISBN: 3346504808 Category : Computers Languages : en Pages : 74
Book Description
Bachelor Thesis from the year 2020 in the subject Computer Science - Miscellaneous, grade: 1.1, University of Constance, language: English, abstract: A lot of data contains implicit hierarchical structures, e.g. type hierarchies. The property graph model – among others employed in some graph databases – provides no tools to capture those internally. In this thesis we derive such hierarchies automatically. First a survey is conducted to find the most promising approaches that cluster a data set hierarchically. In the next step various features and vectors thereof are experimented with to extend the methodology to graphs, capturing the structure as well as possible. We found that there is not one specific feature vector that works well for all data sets and forms of representation in a graph, but rather needs to be constructed adaptive, depending on the way data is modelled. Finally, some extensions of a specific algorithm that was used during experimentation – namely Cobweb – are discussed as well as the use case of cardinality estimation in property graph databases, leveraging the hierarchy as an associative multi-level histogram.
Author: Christopher D. Manning Publisher: Cambridge University Press ISBN: 1139472100 Category : Computers Languages : en Pages :
Book Description
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.
Author: Andrew Gelman Publisher: Cambridge University Press ISBN: 9780521686891 Category : Mathematics Languages : en Pages : 654
Book Description
This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.
Author: Anthony S. Bryk
Author: Anthony S. Bryk
Author: V. Kulish
Author: Stephen W. Raudenbush
Author: Gregory R. Hancock
Author: Ananth Grama
Author: J. Andrew Royle
Author: Rob J Hyndman
Author: Fabian Klopfer
Author: Christopher D. Manning
Author: Andrew Gelman