Simultaneous Statistical Inference and Statistical Power in Survey Research Applications of the General Linear Model PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Simultaneous Statistical Inference and Statistical Power in Survey Research Applications of the General Linear Model PDF full book. Access full book title Simultaneous Statistical Inference and Statistical Power in Survey Research Applications of the General Linear Model by William T. Bielby. Download full books in PDF and EPUB format.
Author: William T. Bielby
Publisher:
ISBN:
Category : Experimental design
Languages : en
Pages : 43
Get Book Here
Book Description
Author: William T. Bielby
Publisher:
ISBN:
Category : Experimental design
Languages : en
Pages : 43
Get Book Here
Book Description
Author: William T. Bielby
Publisher:
ISBN:
Category : Experimental design
Languages : en
Pages : 43
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 408
Get Book Here
Book Description
Author: Michael H. Kutner
Publisher: McGraw-Hill/Irwin
ISBN: 9780072386882
Category : Mathematics
Languages : en
Pages : 1396
Get Book Here
Book Description
Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.
Author: Jacob Cohen
Publisher: Routledge
ISBN: 1134742770
Category : Psychology
Languages : en
Pages : 625
Get Book Here
Book Description
Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
Author: David Sherwyn
Publisher: Kluwer Law International B.V.
ISBN: 9041144390
Category : Law
Languages : en
Pages : 1188
Get Book Here
Book Description
Long regarded as a powerful means to seek individual damages against a corporate defendant, class actions have become a staple of the U.S. litigation system. In recent years, however, several highly significant Supreme Court decisions have weakened the commonality claims of defendants, particularly in workplace discrimination actions. In light of this background, the trends and prospects of employment class actions were the theme of the 56th annual proceedings of the prestigious New York University Conference on Labor, held in May 2003. This important volume reprints the papers presented at that conference, as well as some additional contributions. Among the considerable expertise brought to bear on this controversial subject, readers will find insightful analysis of such issues as the following: Effect of class actions on losing companies; Importance of class actions to Title VII enforcement; Obstacles to class litigation; Compliance and internal enforcement challenges for large employers; Opt-in vs. opt-out alternatives for class members; Value and effectiveness of pattern or practice test cases; Legal limits of group identity; Shifting of the burden of proof; Authority of arbitrators to proceed on a class wide basis; and Countering statistical claims of expert witnesses. Because class actions are based on tension – that between commonality and individuation – they tend to accumulate precedent along a spectrum from disconnected disparity to meaningful resolution. In this deeply informed and thought-provoking book, lawyers and academics concerned with both the interests of employers and of employees will proceed with increased awareness as they work on reconciling the practical and theoretical constraints of class litigation.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 612
Get Book Here
Book Description
Author: Kevin R. Murphy
Publisher: Routledge
ISBN: 1135625328
Category : Psychology
Languages : en
Pages : 247
Get Book Here
Book Description
This book presents a simple and general method for conducting statistical power analysis based on the widely used F statistic. The book illustrates how these analyses work and how they can be applied to problems of studying design, to evaluate others' research, and to choose the appropriate criterion for defining "statistically significant" outcomes. Statistical Power Analysis examines the four major applications of power analysis, concentrating on how to determine: *the sample size needed to achieve desired levels of power; *the level of power that is needed in a study; *the size of effect that can be reliably detected by a study; and *sensible criteria for statistical significance. Highlights of the second edition include: a CD with an easy-to-use statistical power analysis program; a new chapter on power analysis in multi-factor ANOVA, including repeated-measures designs; and a new One-Stop PV Table to serve as a quick reference guide. The book discusses the application of power analysis to both traditional null hypothesis tests and to minimum-effect testing. It demonstrates how the same basic model applies to both types of testing and explains how some relatively simple procedures allow researchers to ask a series of important questions about their research. Drawing from the behavioral and social sciences, the authors present the material in a nontechnical way so that readers with little expertise in statistical analysis can quickly obtain the values needed to carry out the power analysis. Ideal for students and researchers of statistical and research methodology in the social, behavioral, and health sciences who want to know how to apply methods of power analysis to their research.
Author: Zhezhen Jin
Publisher: Springer
ISBN: 3319425714
Category : Medical
Languages : en
Pages : 218
Get Book Here
Book Description
The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking, and innovative clinical trial design and analysis. Each paper was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. It offered 3 keynote speeches, 7 short courses, 76 parallel scientific sessions, student paper sessions, and social events.
Author: Alvin C. Rencher
Publisher: John Wiley & Sons
ISBN: 0470192607
Category : Mathematics
Languages : en
Pages : 690
Get Book Here
Book Description
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.
