# 20 Best Books on Multivariate Modelling

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We have compiled a list of the Best Reference Books on Multivariate Modelling, which are used by students of top universities, and colleges. This will help you choose the right book depending on if you are a beginner or an expert. Here is the complete list of Multivariate Modelling Books with their authors, publishers, and an unbiased review of them as well as links to the Amazon website to directly purchase them. If permissible, you can also download the free PDF books on Multivariate Modelling below.

## 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. advertisement advertisement 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 