1. Applied Multivariate Modelling
|1."Multivariate Models and Multivariate Dependence Concepts" by Harry Joe|
|2."Structural Equation Modeling With Amos: Basic Concepts, Applications, and Programming" by Barbara M Byrne|
“Structural Equation Modeling With Amos: Basic Concepts, Applications, and Programming” Book Review: This book easily illustrates structural equation modelling with AMOS 4.0. The main aim of the book is presenting a nonmathematical introduction to the basic concepts and applications of structural equation modeling. It is written in a simple, user-friendly manner with different 10 SEM applications from model specification to estimation and interpretation of the output. It explains basic applications of SEM using AMOS and highlights features of AMS 4.0. The book contains a schematic representation of the models and statement of the hypothesis being tested in study. It provides a full explanation of related AMOS Graphic input models and output files.
|3."Modelling Non-Stationary Economic Time Series: A Multivariate Approach" by Professor Simon P Burke|
“Modelling Non-Stationary Economic Time Series: A Multivariate Approach” Book Review: This book gives direction and reference to the literature of economics for students and graduate economists. The book covers important concepts such as Cointegration, equilibrium and equilibrium correction in modern applications of econometrics to the real world. It also explains how to identify equilibrium relationships, how to deal with structural breaks associated with regime changes. It demonstrates what to do when variables are of different orders of integration.
|4."On Measuring Global Food Crisis: A Multivariate Modelling Approach" by PARVESH K CHOPRA|
“On Measuring Global Food Crisis: A Multivariate Modelling Approach” Book Review: This book illustrates a new robust multivariate measurement system called Kanji-Chopra Global Food Crisis Measurement System. This book is an essential book for food policy-oriented economists, theorists, researchers, teachers, and informed students.
|5."Modelling Multivariate Survival Data Using Semiparametric Models" by Yau-Wing Lee|
|6."Multivariate Data Analysis" by Hair|
“Multivariate Data Analysis” Book Review: This book provides the information which is required for students to understand and use multivariate data analysis. It also explains an applications-oriented introduction to multivariate analysis for the non-statistician. The book illustrates students how to understand and use the result of statistical techniques.The revised edition of the book contains well-organised chapters with simple language. It also added new chapters based on structural equations modelling. The book also demonstrates advances in technology, capability and different mathematical techniques.
|7."An Introduction to Multivariate Statistical Analysis" by T W Anderson|
“An Introduction to Multivariate Statistical Analysis” Book Review: This book is a good textbook for students and a reference book for professionals who want to learn fundamental knowledge of multivariate statistical analysis. The new edition of the book explains the new advances, elucidating several concepts which are relevant to methodology and comprehension.
|8."Multivariate Analysis and Its Applications" by Kartick Chandra Bhuyan|
|9."Analyzing Multivariate Data" by James M Lattin|
“Analyzing Multivariate Data” Book Review: This book is divided into three sections. The book starts with each important topic by explaining statistical intuition through different applications. Further, it gives numerous illustrative examples for clear understanding. At the end, the book demonstrates related mathematical underpinnings with vectors and matrix algebra. Every chapter follows the same format, it starts with discussing a basic set of research objectives, followed by examples of problems in different fields. The book illustrates an explanation of how each method works, with different application techniques and interpretation of results.
2. Applied Multivariate Statistical Modeling
|1."Applied Multivariate Analysis (Springer Texts in Statistics)" by Neil H Timm|
“Applied Multivariate Analysis (Springer Texts in Statistics)” Book Review: This book gives a comprehensive overview of the basic theory and different methods of applied multivariate analysis. It maintains the balance between both theory and practice. It covers the topics including both the analysis of formal linear multivariate models and exploratory data analysis techniques. Every chapter contains the development of basic theoretical results with different applications. It illustrates different examples from the social and behavioural sciences, and other disciplines.
|2."Handbook of Applied Multivariate Statistics and Mathematical Modeling" by Steven D Brown and Howard E A Tinsley|
“Handbook of Applied Multivariate Statistics and Mathematical Modeling” Book Review: This book demonstrates the different uses of multivariate procedures and mathematical modeling techniques. It explains the practices which enable applied researchers to use procedures effectively without concerning the mathematical basis. The book highlights using different models and statistics as tools. The main goal of the book is to tell readers about which tool to use and which task. Each chapter starts with explanations of what kinds of questions a specific technique can and cannot answer. The book covers different examples including problems of concern in biological and social sciences as well as the humanities.
|3."Multivariate Statistical Analysis in Neuroscience: Advanced Mathematical Modeling Applied to Electroencephalographic Signals in Complex Data Problems" by Giovanni Cugliari and Marco Ivaldi|
|4."Multivariate Statistical Modelling Based on Generalized Linear Models" by Ludwig Fahrmeir and Gerhard Tutz|
“Multivariate Statistical Modelling Based on Generalized Linear Models” Book Review: This book explains the use of generalized linear models for univariate and multivariate regression analysis. It also describes cross sectional analysis, time series and longitudinal data. The book gives an in-depth introduction of the subject based on the analysis of real-world data from different subjects. It also provides available technical details, proofs as an appendix for non-experts. It covers generalized models including models for multi-categorical responses. This is useful for applied statisticians, graduate students of statistics and researchers. The book can also be used for data analysis from different areas of econometrics, biometrics and social sciences.
|5."Applied Univariate, Bivariate, and Multivariate Statistics" by Daniel J Denis|
“Applied Univariate, Bivariate, and Multivariate Statistics” Book Review: This book provides a comprehensive overview of statistical modelling techniques useful in the fields of social and behavioural sciences. The book perfectly illustrates statistical theory and methodology with technical concepts of data analysis. It covers various topics including statistical techniques such as t-tests and correlation. It also explains advanced procedures such as MANOVA, factor analysis, and structural equation modeling with formulas and equations for clear understanding. This is an essential textbook in statistics and methodology at the upper-graduate and graduate-levels in different fields. It can also be useful for researchers and practitioners in various fields.
|6."Applied Multivariate Statistical Analysis" by Richard A Johnson and Dean W Wichern|
“Applied Multivariate Statistical Analysis” Book Review: It is designed for a graduate level course that explains the statistical methods for describing and analyzing multivariate data. The main goal is to give the required knowledge to make good interpretations and select appropriate techniques for multivariate data analysis.
|7."Applied Multivariate Statistical Analysis" by Wolfgang Härdle and Leopold Simar|
“Applied Multivariate Statistical Analysis” Book Review: The book concentrates on high-dimensional applications. It also explains the tools and concepts used in multivariate data analysis in easy language for non-mathematicians and practitioners. Every chapter contains practical exercises which provide applications in various multivariate data analysis fields. All exercises also included R and MATLAB codes which can be found on the website.
|8."Applied Multivariate Statistics for the Social Sciences" by Keenan A Pituch and James P Stevens|
“Applied Multivariate Statistics for the Social Sciences” Book Review: This book provides a practical and theoretical understanding of statistical procedures with different examples and data-sets for advanced students. The new edition of the book explains practical guidelines for data analysis, hypothetical testing, interpreting and reporting results to help students analyze their research data. This book is useful for advanced graduate-level courses in education, psychology, and other social sciences. It can also be useful for researchers as a good reference. It covers multivariate statistics, advanced statistics, or quantitative techniques.
|9."Applied Multivariate Statistical Analysis" by Johnson / Wichern|
|10."Applied Multivariate Statistical Concepts" by Debbie L Hahs-Vaughn|
“Applied Multivariate Statistical Concepts” Book Review: Thik book provides the classic and cutting edge multivariate techniques used in recent research. This book is designed for courses on multivariate statistics, advanced statistics or quarantine techniques studied in psychology, education, sociology, and business. This book is als useful for researchers with no knowledge in multivariate methods. It explains why and how to use each technique with simple writing and real-world examples. Each chapter covers a ‘mathematical snapshot’ which highlights the technical components of each procedure.
|11."Advanced and Multivariate Statistical Methods: Practical Application and Interpretation" by Craig A Mertler|
“Advanced and Multivariate Statistical Methods: Practical Application and Interpretation” Book Review: This book focuses on the conceptual and practical aspects for students who do not need emphasis on the underlying mathematical theory. Students not only learn how to compute the statistics they also learn the logic behind the techniques. The book teaches the reader how to interpret, present, and write up the results for each technique. This book has many problems on the topic along with the solutions available to it allow students to practice their newly acquired skills. There are numerous solved examples to make it easy for students to follow the text. This book covers the topics like Introduction to Multivariate Statistics, A Guide to Multivariate Techniques, Pre-Analysis Data Screening, Factorial Analysis of Variance, Analysis of Covariance, Multivariate Analysis of Variance and Covariance, Multiple Regression, Path Analysis, Factor Analysis, Discriminant Analysis, Logistic Regression along with some appendices.