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Testing Research Hypotheses With The General Linear Model
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Book Synopsis Testing Research Hypotheses with the General Linear Model by : Keith A. McNeil
Download or read book Testing Research Hypotheses with the General Linear Model written by Keith A. McNeil and published by SIU Press. This book was released on 1996 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Briefly describes 777 serial bibliographies relating to modern literature in most of the major languages. Chapters cover comprehensive bibliographies, those for English and foreign literatures, for topics from African American studies to women's studies, and for particular authors. The 1982 edition has been updated and expanded to include information on electronic serial bibliographies. Paper edition (unseen), $19.75. Annotation copyright by Book News, Inc., Portland, OR
Book Synopsis Testing Research Hypotheses with the General Linear Regression by : Keith A. McNeil
Download or read book Testing Research Hypotheses with the General Linear Regression written by Keith A. McNeil and published by . This book was released on 1975 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Designing General Linear Models to Test Research Hypotheses by : Keith A. McNeil
Download or read book Designing General Linear Models to Test Research Hypotheses written by Keith A. McNeil and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors discuss General Linear Models specifically designed to statistically test research hypotheses that deal with the differences among group means, relationships between continuous variables, analysis of covariance, interaction effects, nonlinear relationships, and repeated measures. Illustrations of the various analyses using Microsoft Excel and SPSS for Windows are presented.
Book Synopsis Hypothesis Testing in the General Linear Model by : Olga P. Hackney
Download or read book Hypothesis Testing in the General Linear Model written by Olga P. Hackney and published by . This book was released on 1976 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sample Size Choice by : Robert E. Odeh
Download or read book Sample Size Choice written by Robert E. Odeh and published by CRC Press. This book was released on 2020-08-12 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to testing statistical hypotheses for readers familiar with the Neyman-Pearson theory of hypothesis testing including the notion of power, the general linear hypothesis (multiple regression) problem, and the special case of analysis of variance. The second edition (date of first not mentione
Book Synopsis Testing Research Hypotheses Using Multiple Linear Regression by : Keith A. McNeil
Download or read book Testing Research Hypotheses Using Multiple Linear Regression written by Keith A. McNeil and published by . This book was released on 1975 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple regression is becomingmore widely used as the statistical technique for answering research hypotheses. This is so for several reasons: 1) the technique is extremely versatile; 2) the computer has made the technique more available to researchers; and 3) texts such as the authors' earlier work are making the technique more available to researchers. The statistical technique of multiple regression allows the inclusion of numerous continuous (quantitative) and categorical (qualitative) variables in the prediction of some criterion. Appendixes contain a multiple regression computer program and data on which the problems are based; a discussion of the similarities and differences between analysis of variance and multiple regression; and a computer program providing the regression solution to natural language research hypotheses.
Book Synopsis The Linear Hypothesis by : George Arthur Frederick Seber
Download or read book The Linear Hypothesis written by George Arthur Frederick Seber and published by . This book was released on 1980 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Linear Model and Hypothesis by : George Seber
Download or read book The Linear Model and Hypothesis written by George Seber and published by Springer. This book was released on 2015-10-08 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a concise and integrated overview of hypothesis testing in four important subject areas, namely linear and nonlinear models, multivariate analysis, and large sample theory. The approach used is a geometrical one based on the concept of projections and their associated idempotent matrices, thus largely avoiding the need to involvematrix ranks. It is shown that all the hypotheses encountered are either linear or asymptotically linear, and that all the underlying models used are either exactly or asymptotically linear normal models. This equivalence can be used, for example, to extend the concept of orthogonality to other models in the analysis of variance, and to show that the asymptotic equivalence of the likelihood ratio, Wald, and Score (Lagrange Multiplier) hypothesis tests generally applies.
Book Synopsis Multivariate General Linear Models by : Richard F. Haase
Download or read book Multivariate General Linear Models written by Richard F. Haase and published by SAGE. This book was released on 2011-11-23 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title provides an integrated introduction to multivariate multiple regression analysis (MMR) and multivariate analysis of variance (MANOVA). It defines the key steps in analyzing linear model data and introduces multivariate linear model analysis as a generalization of the univariate model. Richard F. Haase focuses on multivariate measures of association for four common multivariate test statistics, presents a flexible method for testing hypotheses on models, and emphasizes the multivariate procedures attributable to Wilks, Pillai, Hotelling, and Roy.
Book Synopsis Parameter Estimation and Hypothesis Testing in Linear Models by : Karl-Rudolf Koch
Download or read book Parameter Estimation and Hypothesis Testing in Linear Models written by Karl-Rudolf Koch and published by Springer Science & Business Media. This book was released on 1999-04 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: The necessity to publish the second edition of this book arose when its third German edition had just been published. This second English edition is there fore a translation of the third German edition of Parameter Estimation and Hypothesis Testing in Linear Models, published in 1997. It differs from the first English edition by the addition of a new chapter on robust estimation of parameters and the deletion of the section on discriminant analysis, which has been more completely dealt with by the author in the book Bayesian In ference with Geodetic Applications, Springer-Verlag, Berlin Heidelberg New York, 1990. Smaller additions and deletions have been incorporated, to im prove the text, to point out new developments or to eliminate errors which became apparent. A few examples have been also added. I thank Springer-Verlag for publishing this second edition and for the assistance in checking the translation, although the responsibility of errors remains with the author. I also want to express my thanks to Mrs. Ingrid Wahl and to Mrs. Heidemarlen Westhiiuser who prepared the second edition. Bonn, January 1999 Karl-Rudolf Koch Preface to the First Edition This book is a translation with slight modifications and additions of the second German edition of Parameter Estimation and Hypothesis Testing in Linear Models, published in 1987.
Book Synopsis Biostatistics for Animal Science, 3rd Edition by : Miroslav Kaps
Download or read book Biostatistics for Animal Science, 3rd Edition written by Miroslav Kaps and published by CABI. This book was released on 2017-06-23 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed to cover techniques for analysis of data in the animal sciences, this popular textbook provides an overview of the basic principles of statistics enabling the subsequent applications to be carried out with familiarity and understanding. Each chapter begins by introducing a problem with practical questions, followed by a brief theoretical background. Most topics are followed up with numerical examples to illustrate the methods described using data-sets from animal sciences and related fields. The same examples are then solved using the SAS software package. Written primarily for students and researchers in animal sciences, the text is also useful for those studying agricultural, biological, and veterinary sciences.
Book Synopsis Topics on Multiple Hypotheses Testing and Generalized Linear Model by : Yalin Zhu
Download or read book Topics on Multiple Hypotheses Testing and Generalized Linear Model written by Yalin Zhu and published by . This book was released on 2017 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: In applications such as studying drug adverse events (AE) in clinical trials and identifying differentially expressed genes in microarray experiments, the data of the experiments usually consists of frequency counts. In the analysis of such data, researchers often face multiple hypotheses testing based on discrete test statistics. Incorporating this discrete property of the data, several stepwise procedures, which allow to use the CDF of p-values to determine the testing threshold, are proposed for controlling familiwise error rate (FWER). It is shown that the proposed procedures strongly control the FWER and are more powerful than the existing ones for discrete data. Through some simulation studies and real data examples, the proposed procedures are shown to outperform the existing procedures in terms of the FWER control and power. An R package “MHTdiscrete” and a web application are developed for implementing the proposed procedures for discrete data.
Book Synopsis The Routledge Encyclopedia of Research Methods in Applied Linguistics by : A. Mehdi Riazi
Download or read book The Routledge Encyclopedia of Research Methods in Applied Linguistics written by A. Mehdi Riazi and published by Routledge. This book was released on 2016-01-13 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Routledge Encyclopedia of Research Methods in Applied Linguistics provides accessible and concise explanations of key concepts and terms related to research methods in applied linguistics. Encompassing the three research paradigms of quantitative, qualitative, and mixed methods, this volume is an essential reference for any student or researcher working in this area. This volume provides: A–Z coverage of 570 key methodological terms from all areas of applied linguistics; detailed analysis of each entry that includes an explanation of the head word, visual illustrations, cross-references to other terms, and further references for readers; an index of core concepts for quick reference. Comprehensively covering research method terminology used across all strands of applied linguistics, this encyclopedia is a must-have reference for the applied linguistics community.
Book Synopsis Linear Models in Statistics by : Alvin C. Rencher
Download or read book Linear Models in Statistics written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2008-01-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.
Book Synopsis Simultaneous Statistical Inference and Statistical Power in Survey Research Applications of the General Linear Model by : William T. Bielby
Download or read book Simultaneous Statistical Inference and Statistical Power in Survey Research Applications of the General Linear Model written by William T. Bielby and published by . This book was released on 1976 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The SAGE Encyclopedia of Social Science Research Methods by : Michael Lewis-Beck
Download or read book The SAGE Encyclopedia of Social Science Research Methods written by Michael Lewis-Beck and published by SAGE. This book was released on 2004 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.
Book Synopsis Testing Hypotheses in Linear Models with Weighted Rank Statistics by : G. L. Sievers
Download or read book Testing Hypotheses in Linear Models with Weighted Rank Statistics written by G. L. Sievers and published by . This book was released on 1983 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tests of hypotheses for the parameters in a general linear model are considered based on weighted rank statistics. Results are presented for tests based on a rank estimate, tests based on drop in dispersion and aligned rank tests. Weights can be used to focus the analysis on simple effects and provide an additional degree of robustness to rank tests. Several analysis of variance applications are discussed. (Author).
