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Linear Mixed Models, Galecki, Andrzej T,Welch, Kathleen B.,West, Brady T., 97814
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- Compralo SubitoLinear Mixed Models, Galecki, Andrzej T,Welch, Kathleen B.,West, Brady T., 97814
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Specifiche dell'oggetto
- Condizione
- Book Title
- Linear Mixed Models
- ISBN
- 9781466560994
Informazioni su questo prodotto
Product Identifiers
Publisher
CRC Press LLC
ISBN-10
1466560991
ISBN-13
9781466560994
eBay Product ID (ePID)
117173705
Product Key Features
Number of Pages
440 Pages
Language
English
Publication Name
Linear Mixed Models : a Practical Guide Using Statistical Software, Second Edition
Subject
Probability & Statistics / General
Publication Year
2014
Type
Textbook
Subject Area
Mathematics
Format
Hardcover
Dimensions
Item Height
0.9 in
Item Weight
33.7 Oz
Item Length
13.5 in
Item Width
6.9 in
Additional Product Features
Edition Number
2
Intended Audience
College Audience
LCCN
2014-010347
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
519.5/35
Edition Description
Revised edition,New Edition
Table Of Content
INTRODUCTION What Are Linear Mixed Models (LMMs)? A Brief History of Linear Mixed Models LINEAR MIXED MODELS: AN OVERVIEW Introduction Specification of LMMs The Marginal Linear Model Estimation in LMMs Computational Issues Tools for Model Selection Model-Building Strategies Checking Model Assumptions (Diagnostics) Other Aspects of LMMs Power Analysis for Linear Mixed Models Chapter Summary TWO-LEVEL MODELS FOR CLUSTERED DATA: THE RAT PUP EXAMPLE Introduction The Rat Pup Study Overview of the Rat Pup Data Analysis Analysis Steps in the Software Procedures Results of Hypothesis Tests Comparing Results across the Software Procedures Interpreting Parameter Estimates in the Final Model Estimating the Intraclass Correlation Coefficients (ICCs) Calculating Predicted Values Diagnostics for the Final Model Software Notes and Recommendations THREE-LEVEL MODELS FOR CLUSTERED DATA; THE CLASSROOM EXAMPLE Introduction The Classroom Study Overview of the Classroom Data Analysis Analysis Steps in the Software Procedures Results of Hypothesis Tests Comparing Results across the Software Procedures Interpreting Parameter Estimates in the Final Model Estimating the Intraclass Correlation Coefficients (ICCs) Calculating Predicted Values Diagnostics for the Final Model Software Notes Recommendations MODELS FOR REPEATED-MEASURES DATA: THE RAT BRAIN EXAMPLE Introduction The Rat Brain Study Overview of the Rat Brain Data Analysis Analysis Steps in the Software Procedures Results of Hypothesis Tests Comparing Results across the Software Procedures Interpreting Parameter Estimates in the Final Model The Implied Marginal Variance-Covariance Matrix for the Final Model Diagnostics for the Final Model Software Notes Other Analytic Approaches Recommendations RANDOM COEFFICIENT MODELS FOR LONGITUDINAL DATA: THE AUTISM EXAMPLE Introduction The Autism Study Overview of the Autism Data Analysis Analysis Steps in the Software Procedures Results of Hypothesis Tests Comparing Results across the Software Procedures Interpreting Parameter Estimates in the Final Model Calculating Predicted Values Diagnostics for the Final Model Software Note: Computational Problems with the D Matrix An Alternative Approach: Fitting the Marginal Model with an Unstructured Covariance Matrix MODELS FOR CLUSTERED LONGITUDINAL DATA: THE DENTAL VENEER EXAMPLE Introduction The Dental Veneer Study Overview of the Dental Veneer Data Analysis Analysis Steps in the Software Procedures Results of Hypothesis Tests Comparing Results across the Software Procedures Interpreting Parameter Estimates in the Final Model The Implied Marginal Variance-Covariance Matrix for the Final Model Diagnostics for the Final Model Software Notes and Recommendations Other Analytic Approaches MODELS FOR DATA WITH CROSSED RANDOM FACTORS: THE SAT SCORE EXAMPLE Introduction The SAT Score Study Overview of the SAT Score Data Analysis Analysis Steps in the Software Procedures Results of Hypothesis Tests Comparing Results across the Software Procedures Interpreting Parameter Estimates in the Final Model The Implied Marginal Variance-Covariance Matrix for the Final Model Recommended Diagnostics for the Final Model Software Notes and Additional Recommendations APPENDIX A: STATISTICAL SOFTWARE RESOURCES APPENDIX B: CALCULATION OF THE MARGINAL VARIANCE-COVARIANCE MATRIX APPENDIX C: ACRONYMS/ABBREVIATIONS BIBLIOGRAPHY INDEX
Synopsis
Highly recommended by JASA, Technometrics , and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM. New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggested approaches to writing simulations Use of the lmer() function in the lme4 R package New sections on fitting LMMs to complex sample survey data and Bayesian approaches to making inferences based on LMMs Updated graphical procedures in the software packages Substantially revised index to enable more efficient reading and easier location of material on selected topics or software options More practical recommendations on using the software for analysis A new R package (WWGbook) that contains all of the data sets used in the examples Ideal for anyone who uses software for statistical modeling, this book eliminates the need to read multiple software-specific texts by covering the most popular software programs for fitting LMMs in one handy guide. The authors illustrate the models and methods through real-world examples that enable comparisons of model-fitting options and results across the software procedures., Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM. New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggested approaches to writing simulations Use of the lmer() function in the lme4 R package New sections on fitting LMMs to complex sample survey data and Bayesian approaches to making inferences based on LMMs Updated graphical procedures in the software packages Substantially revised index to enable more efficient reading and easier location of material on selected topics or software options More practical recommendations on using the software for analysis A new R package (WWGbook) that contains all of the data sets used in the examples Ideal for anyone who uses software for statistical modeling, this book eliminates the need to read multiple software-specific texts by covering the most popular software programs for fitting LMMs in one handy guide. The authors illustrate the models and methods through real-world examples that enable comparisons of model-fitting options and results across the software procedures.
LC Classification Number
QA279.W47 2014
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Feedback sul venditore (38.760)
- e***v (129)- Feedback lasciato dall'acquirente.Ultimi 6 mesiAcquisto verificatoOverall, it went well. Good communication. I wanted the book to be shipped in a box, because the value and scarcity of the volume I purchased deserved it, however, the company is too large and I was informed the book would be shipped in a plastic mailer. Somehow it didn’t arrive very damaged, a little bump, but for the price I can’t complain. Over all I am satisfied, but if you’re a book collector, as I am, you may want to find another seller.Aurora: The Dayspring, or Dawning of the Day in the East, Boehme, Jacob, 9781558 (N° 236039083546)
- 1***j (84)- Feedback lasciato dall'acquirente.Mese scorsoAcquisto verificatoGreat experience. Seller responded promptly with quick shipping. The item was well packaged. The seller was great. Prices and descriptions of the merchandise were accurate.
- s***a (782)- Feedback lasciato dall'acquirente.Ultimi 6 mesiAcquisto verificatoThis company has been, in my experience, a mixed bag. This title was NOT worth the price because it came with highlighting, ink underlineing & writing in the margins...not the quality that they advertised. I have on other occasions gotten books in great condition, however, that were listed in less than the condition advertised so it goes both ways...but I'd much prefer a company that delivers exactly what they advertise. I guess good help is hard to find. The book was well packaged & came fast.