Book Description
This book takes a practical approach to multivariate data analysis, with an introduction to the most commonly encountered statistical and multivariate techniques.
Using Multivariate Statistics provides practical guidelines for conducting numerous types of multivariate statistical analyses. It gives syntax and output for accomplishing many analyses through the most recent releases of SAS, SPSS, and SYSTAT, some not available in software manuals. The book maintains its practical approach, still focusing on the benefits and limitations of applications of a technique to a data set - when, why, and how to do it. Overall, it provides advanced users with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics.
For those interested in statistical analysis.
Book Description
Packed with concrete examples, Hatcher's book provides an introduction to more advanced statistical procedures and includes handy appendices that give basic instruction in using the SAS System. Novice SAS users will find all they need to master SAS basics and move into advanced statistical analyses in this one book. Featured is a simple, step-by-step approach to testing structural equation models with latent variables using the CALIS procedure. The following topics are explained in easy-to-understand terms: exploratory factor analysis, principal component analysis, and developing measurement models with confirmatory factor analysis. Other covered topics of note include "LISREL-type" analyses with the user-friendly PROC CALIS and solving problems encountered in real-world social science research.
Supports releases 6.09 and higher of SAS software.
Customer Reviews:
Very Good .......2007-08-06
More detailed explanation of every subject discussed. Nothing was assummed. The appendix include vital information for new SAS users.
Absolutely outstanding.......2007-05-23
This is the single best statistics text I've ever read. It's extremely easy to follow, very practical, and gives outstanding examples. Everything is so clearly described in the book that one might call it Factor analysis and SEM for Dummies. I only wish that the book covered nonrecursive SEM models.
Easy to read.......2006-11-03
Very easy to read. Examples are simple and effective. The book explains the statistical concepts as well as the SAS programming tricks. In fact, the book provides complete code - you will be able to get good amount of analysis done just by copying that code. However, you also need to buy the "The Little SAS Book" if you never used SAS before.
Excellent book.......2003-05-01
This outstanding book was one of the mainstays for my Ph.D. dissertation. It explain factor analysis and SEM techniques in a clear and effective way, with an hands-on approach that guides the reader during all the data analysis and result interpretation phases.
Thank goodness for this book.......2002-10-21
I really needed this for my dissertation. As a computer scientist who is using statistically-based data mining techniques in my PhD dissertation, I needed a good "Quick Course" in factor analysis. More important than just "what is factor analysis", I needed to know how to implement my ideas in SAS. This book did the trick. Now let's hope my advisors think so. :)
Book Description
Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on both general and hierarchical model specifications, develop the model-building process step-by-step, and demonstrate the estimation, testing, and interpretation of fixed-effect parameters and covariance parameters associated with random effects. These concepts are illustrated through examples using real-world data sets that enable comparisons of model fitting options and results across the software procedures. The book also gives an overview of important options and features available in each procedure. Making popular software procedures for fitting LMMs easy-to-use, this valuable resource shows how to perform LMM analyses and provides a clear explanation of mixed modeling techniques and theories.
Product Description
Updated for SAS®9, this second edition is an easy-to-understand introduction to SAS as well as to univariate and multivariate statistics. Clear explanations and simple language guide you through the research terminology, data input, data manipulation, and types of statistical analysis that are most commonly used in the social and behavioral sciences. Providing practice data inspired by actual studies, this book teaches you how to choose the right statistic, understand the assumptions underlying the procedure, prepare the SAS program for the analysis, interpret the output, and summarize the analysis and results according to the format prescribed in the Publication Manual of the American Psychological Association. Step by step you will learn how to perform the following types of analysis: simple descriptive statistics, measures of bivariate association, t tests: independent samples and paired samples, NOVA and MANOVA, multiple regression, principal component analysis, and assessing scale reliability with coefficient alpha. This text is ideally suited to students who are beginning their study of data analysis, and to professors and researchers who want a handy reference on their bookshelf.
Customer Reviews:
learning common tests in SAS.......2005-09-04
O'Rouke tackles a disconnect that arises naturally between statistics texts and SAS. The former talk in general terms about many important statistical tests, for univariate and multivariate distributions. From books like these, programmers at SAS built up massive libraries that implemented those tests.
Yet to someone outside SAS, who might be a student or professional statistician, knowing in general is often little help in being able to do specific tests in SAS. So O'Rouke wrote what you might think of as a standard text. Except that it is firmly grounded in showing how all this can be done in SAS. It is also suitable as a first text in those tests. In fact, maybe even better than standard texts. Because this book gives you the tools to familiarise yourself with easily running those tests against data sets. Typically, the other books leave you with two things to do. Write those tests (or get software from someone), and apply these against data.
Book Description
A user-friendly guide beneficial to both researchers and students of the social sciences, this book provides a very comprehensive introduction of the SAS System and elementary statistical procedures. Step by step, this book guides beginners through the basic concepts of research and data analysis, to data input and on to ANOVA and MANOVA. The more advanced researchers will find the presentation of sophisticated statistical procedures invaluable. With this book you will learn to write SAS programs, interpret results, perform statistical analyses without a broad mathematics background, and summarize results in American Psychological Association format.
Supports releases 6.07 and higher of SAS software.
Customer Reviews:
NOT good for learning/understanding statistics.......2002-08-05
The book was targetted to social scientists. The reviewer is from physical sciences. Thus this review may be biased.
Either the authors tried not to confuse novices in statistics with too much theory/math, or they assumed the readers are fluent with statistics but are tyros in SAS. The book included as little formula and derivations as possible. I find it is hard to understand what is really going on and why the procedures do things in those ways. It reminds me certain cook books. If you are desperately 'hungry', this might be a good one for you. However, if you want to be a chef, look somewhere else.
I am not sure how social scientists will feel about this book. As a statistician, I think this is definitely NOT a book for those who are comfortable with mathematical derivations, i.e. most mathematicians, statisticians and physicists.
One of my favorite statistical reference books.......2000-06-04
You do not need to be a social scientist nor use SAS to find this book helpful. I am not a social scientist, and often use other statistical software. Still, I use this guide more than any of my other statistical textbooks and reference books. The authors do an excellent job of explaining how to perform and interpret a variety of statistical tests. For SAS users, there are many example programs and instructions on how to write and interpret these. If you regularly use statistics in your schooling or career, this book is a must have!
Book Description
A highly readable introduction,
Using LISREL for Structural Equation Modeling is for researchers and graduate students in the social sciences who require structural equation modeling techniques to answer substantive research questions. Author E. Kevin Kelloway provides an overview of structural equation modeling including the theory and logic of structural equation models (SEMs), assessing the "fit" of SEMs to the data, and implementation of SEMs in the LISREL environment. Specific applications of SEMs are considered including confirmatory factor analysis, observed variable path analysis, and latent variable path analysis. A sample application including the source code, printout, and results section is presented for each type of analysis. Tricks of the trade for structural equation modeling are presented including the use of single indicator latent variable and reducing the cognitive complexity of models.
Customer Reviews:
Good but intorductory overview.......2001-05-16
This is a good beginner's guide to SEM and LISREL. The author explains the concepts in a very understandable manner. Although I bought this book two years back, I still refer back to it occasionally. I would highly recommend this to someone who is just starting out with SEM. But more advanced users will be a little disappointed because it stops at the basics. Two notes of warning are in order: (1) this book does NOT discuss the visual interface that LISREL now has, and (2) SPSS now supports AMOS and has dropped LISREL support.
Not just about LISREL.......1999-05-25
In teaching structural equation modeling in a doctoral-level graduate class, I found Kelloway's book one of the most useful resources. Despite its title, the book is not only about LISREL. The initial chapters provide an excellent overview of the science (and art) of structural equation modeling. Kelloway provides probably a better summary than most other books on the topic.
A worthy guide to non-specialists.......1999-02-20
If your goal is to use LISREL and apply structural equation modeling to your own work, this is the book for you. Goes over the model and the software in enough detail to handle most of the problems my stats students see, and is clearly written and easy to follow.
Book Description
Includes practical elements of matrix theory, continuous multivariate distributions and basic multivariate statistics in the normal distribution; regression and the analysis of variance; factor analysis and latent structure analysis; canonical correlations; stable portfolio analysis; classifications and discrimination models; control in the multivariate linear model; and structuring multivariate populations. 1982 edition.
Customer Reviews:
Applied Multivariate Analysis : Using Bayesian and Frequentist Methods of Inference. Second edition.......2006-02-06
Good quality & delivery, sold at reasonable price
Book Description
Conducting Meta-Analysis Using SAS reviews the meta-analysis statistical procedure and shows the reader how to conduct one using SAS. It presents and illustrates the use of the PROC MEANS procedure in SAS to perform the data computations called for by the two most commonly used meta-analytic procedures, the Hunter & Schmidt and Glassian approaches.
This book serves as both an operational guide and user's manual by describing and explaining the meta-analysis procedures and then presenting the appropriate SAS program code for computing the pertinent statistics. The practical, step-by-step instructions quickly prepare the reader to conduct a meta-analysis. Sample programs available on the Web further aid the reader in understanding the material.
Intended for researchers, students, instructors, and practitioners interested in conducting a meta-analysis, the presentation of both formulas and their associated SAS program code keeps the reader and user in touch with technical aspects of the meta-analysis process. The book is also appropriate for advanced courses in meta-analysis psychology, education, management, and other applied social and health sciences departments.
Customer Reviews:
Limited usefulness.......2005-05-14
The focus of this book on Glassian (d) and Hunter and Schmidt (r) approaches to meta-analysis really limits the usefulness of the book. Examples are limited to social sciences literature in which these approaches have been used. Do not buy if you want techniques publishable in other literatures.
Book Description
The study of the statistics of extreme events is an essential first step in the mitigation of natural catastrophies, that often cause severe economic losses worldwide. This book is about the theoretical and practical aspects of the statistics of Extreme Events in Nature.
Most importantly, this is the first text in which Copulas are introduced and used in Geophysics.
Several topics are fully original, and show how standard models and calculations can be improved by exploiting the opportunities offered by Copulas. In addition, new quantities useful for design and risk assessment are introduced. Practicioners in all research areas of Geosciences and extreme events (including Finance and Insurance, closely related to natural disasters) will definitely benefit from the new Copula-approach outlined in the book.
This volume will be of interest to researchers and practitioners in the fields of civil and environmental engineering, geophysics, geosciences, geography and environmental science. Also scientists and undergraduate up to post graduate level students in water resources and hydrology will find valuable information in this book.
Book Description
Multivariate statistical methods are described in this study and advice is given on how best to apply these methods using CANOCO software. Data sets and program files for the case studies are provided on a supporting website. The book is useful to anyone studying complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulations. It is primarily targeted at ecologists who need to analyze data resulting from field observations and experiments.
Download Description
This book is primarily written for ecologists needing to analyse data resulting from field observations and experiments. It will be particularly useful for students and researchers dealing with complex ecological problems, such as the variation of biotic communities with environmental conditions or the response of biotic communities to experimental manipulation. Following a simple introduction to ordination methods, the text focuses on constrained ordination methods (RDA, CCA) and the use of permutation tests on statistical hypotheses of multivariate data. An overview of classification methods, or modern regression methods (GLM, GAM, loess), is provided and guidance on the correct interpretation of ordination diagrams is given. Seven case studies of varying difficulty help to illustrate the suggested analytical methods, using the Canoco for Windows software. The case studies utilise both the descriptive and manipulative approaches, and they are supported by data sets and project files available from the book website.
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- Artificial Intelligence: A Modern Approach (2nd Edition)
- Beyond Software Architecture: Creating and Sustaining Winning Solutions
- Biology, Sixth Edition
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General
| Social Sciences
| Nonfiction
| Subjects
| Books
Reading & Understanding Multivariate Statistics
SPSS Survival Manual
Applied Multiple Regression - Correlation Analysis for the Behavioral Sciences
Principles and Practice of Structural Equation Modeling, Second Edition (Methodology In The Social Sciences)
Reading And Understanding More Multivariate Statistics
