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Author : Ayesha Nneka Delpish
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (713 download)
Download or read book A Comparison of Estimators in Hierarchical Linear Modeling written by Ayesha Nneka Delpish and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kathleen H. Harrow
Publisher :
ISBN 13 :
Total Pages : 434 pages
Book Rating : 4.:/5 (78 download)
Download or read book A Comparison of Three Estimation Methods for Hierarchical Linear Models written by Kathleen H. Harrow and published by . This book was released on 2002 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : G. David Garson
Publisher : SAGE
ISBN 13 : 1412998859
Total Pages : 393 pages
Book Rating : 4.4/5 (129 download)
Download or read book Hierarchical Linear Modeling written by G. David Garson and published by SAGE. This book was released on 2013 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a brief, easy-to-read guide to implementing hierarchical linear modeling using three leading software platforms, followed by a set of original how-to applications articles following a standardard instructional format. The "guide" portion consists of five chapters by the editor, providing an overview of HLM, discussion of methodological assumptions, and parallel worked model examples in SPSS, SAS, and HLM software. The "applications" portion consists of ten contributions in which authors provide step by step presentations of how HLM is implemented and reported for introductory to intermediate applications.
Author : Stephen W. Raudenbush
Publisher : SAGE
ISBN 13 : 9780761919049
Total Pages : 520 pages
Book Rating : 4.9/5 (19 download)
Download or read book Hierarchical Linear Models written by Stephen W. Raudenbush and published by SAGE. This book was released on 2002 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Bernd-Wolfgang Igl
Publisher :
ISBN 13 :
Total Pages : 91 pages
Book Rating : 4.:/5 (752 download)
Download or read book A Comparison of Two Estimators in Multivariate Linear Models with Errors-in-variables written by Bernd-Wolfgang Igl and published by . This book was released on 2005 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Anthony S. Bryk
Publisher : SAGE Publications, Incorporated
ISBN 13 :
Total Pages : 296 pages
Book Rating : 4.F/5 ( download)
Download or read book Hierarchical Linear Models written by Anthony S. Bryk and published by SAGE Publications, Incorporated. This book was released on 1992 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Steven M. Sidik
Publisher :
ISBN 13 :
Total Pages : 50 pages
Book Rating : 4.:/5 (31 download)
Download or read book Comparison of Some Biased Estimation Methods (including Ordinary Subset Regression) in the Linear Model written by Steven M. Sidik and published by . This book was released on 1975 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Roger A. Horn
Publisher :
ISBN 13 :
Total Pages : 48 pages
Book Rating : 4.:/5 (227 download)
Download or read book Comparison of Estimators of Heteroscedastic Variances in Linear Models written by Roger A. Horn and published by . This book was released on 1973 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: Three methods for estimating heteroscedastic variances are discussed in the paper: the MINQUE introduced by C.R. Rao, the AUE introduced by Duncan, Horn, and Horn, and the sample variance. Properties of these estimators, including translation invariance, existence, bias, consistency, existence of negative estimates, and mean square error are compared. In particular, it is shown that the AUE has smaller mean square error than either the MINQUE or the sample variance in a wide range of situations. (Author).
Author : Tom A. B. Snijders
Publisher : SAGE
ISBN 13 : 9780761958901
Total Pages : 282 pages
Book Rating : 4.9/5 (589 download)
Download or read book Multilevel Analysis written by Tom A. B. Snijders and published by SAGE. This book was released on 1999 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel analysis covers all the main methods, techniques and issues for carrying out multilevel modeling and analysis. The approach is applied, and less mathematical than many other textbooks.
Author : Kenneth D. West
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (119 download)
Download or read book A Comparison of Alternative Instruments Variables Estimators of a Dynamic Linear Model written by Kenneth D. West and published by . This book was released on 1995 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using a dynamic linear equation that has a conditionally homoskedastic moving average disturbance, we compare two parameterizations of a commonly used instrumental variables estimator (Hansen (1982)) to one that is asymptotically optimal in a class of estimators that includes the conventional one (Hansen (1985)). We find that for some plausible data generating processes, the optimal one is distinctly more efficient asymptotically. Simulations indicate that in samples of size typically available, asymptotic theory describes the distribution of the parameter estimates reasonably well, but that test statistics sometimes are poorly sized.
Author : Timo Teräsvirta
Publisher :
ISBN 13 : 9789514519420
Total Pages : 11 pages
Book Rating : 4.5/5 (194 download)
Download or read book A Comparison of Mixed and Minimax Estimators of Linear Models written by Timo Teräsvirta and published by . This book was released on 1980 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Truman Orville Lewis
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 216 pages
Book Rating : 4.3/5 (97 download)
Download or read book Estimation in Linear Models written by Truman Orville Lewis and published by Prentice Hall. This book was released on 1971 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Marvin H. J. Gruber
Publisher : Academic Press
ISBN 13 : 1483260976
Total Pages : 361 pages
Book Rating : 4.4/5 (832 download)
Download or read book Regression Estimators written by Marvin H. J. Gruber and published by Academic Press. This book was released on 2014-05-10 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression Estimators: A Comparative Study presents, compares, and contrasts the development and the properties of the ridge type estimators that result from both Bayesian and non-Bayesian (frequentist) methods. The book is divided into four parts. The first part (Chapters I and II) discusses the need for alternatives to least square estimators, gives a historical survey of the literature and summarizes basic ideas in Matrix Theory and Statistical Decision Theory used throughout the book. The second part (Chapters III and IV) covers the estimators from both the Bayesian and from the frequentist points of view and explores the mathematical relationships between them. The third part (Chapters V-VIII) considers the efficiency of the estimators with and without averaging over a prior distribution. Part IV, the final two chapters IX and X, suggests applications of the methods and results of Chapters III-VII to Kaiman Filters and Analysis of Variance, two very important areas of application. Statisticians and workers in fields that use statistical methods who would like to know more about the analytical properties of ridge type estimators will find the book invaluable.
Author : Mathias Harrer
Publisher : CRC Press
ISBN 13 : 1000435636
Total Pages : 500 pages
Book Rating : 4.0/5 (4 download)
Download or read book Doing Meta-Analysis with R written by Mathias Harrer and published by CRC Press. This book was released on 2021-09-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book
Author : Stuart Maxwell Angus
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (871 download)
Download or read book An comparison of the jacknife and bootstrap estimators in linear models, with reference to production models used by Sasol written by Stuart Maxwell Angus and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Hardeo Sahai
Publisher : Springer Science & Business Media
ISBN 13 : 0817644253
Total Pages : 493 pages
Book Rating : 4.8/5 (176 download)
Download or read book Analysis of Variance for Random Models, Volume 2: Unbalanced Data written by Hardeo Sahai and published by Springer Science & Business Media. This book was released on 2007-07-03 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systematic treatment of the commonly employed crossed and nested classification models used in analysis of variance designs with a detailed and thorough discussion of certain random effects models not commonly found in texts at the introductory or intermediate level. It also includes numerical examples to analyze data from a wide variety of disciplines as well as any worked examples containing computer outputs from standard software packages such as SAS, SPSS, and BMDP for each numerical example.
Author : Daniel Navarro
Publisher : Lulu.com
ISBN 13 : 1326189727
Total Pages : 617 pages
Book Rating : 4.3/5 (261 download)
Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
