Analysis, Quantitative Analysis
Multivariate analysis is a form of quantitative
analysis which examines three or more variables at the same time, in order to
understand the relationships among them.
The simplest form of multivariate analysis is one in which the researcher,
interested in the relationship between an independent variable and a dependent variable
(eg: gender and political attitudes), introduces an extraneous variable (eg: age) to
ensure that a correlation between the two main variables is not spurious.
Presented in tabular form multivariate analysis divides the age variable into its
constituent values (eg: young and old) and then subdivides each of these values into the
values of female and male. Having done this it is possible to determine whether there is a
correlation, among young people, between the variables of gender and political attitudes.
Other forms of multivariate analysis are examined in methodology
texts under the heading of the elaboration model, and here one finds conditional
variables, intervening variables, extraneous variables.
As the name indicates, multivariate analysis comprises a set of techniques
dedicated to the analysis of data sets with more than one variable. Several of these
techniques were developed recently in part because they require the computational
capabilities of modern computers. Also, because most of them are recent, these techniques
are not always uni?ed in their presentation, and the choice of the proper technique for a
given problem is often difficult.
This article provides a (non-exhaustive) catalog in order to help decide when to use a
given statistical technique for a given type of data or statistical question and gives a
brief description of each technique. This paper is organized according to the number of
data sets to analyze: one or two (or more). With two data sets we consider two cases: in
the ?rst case, one set of data plays the role of predictors (or independent) variables
(IVs) and the second set of data corresponds to measurements or dependent variables
(DVs); in the second case, the different sets of data correspond to di?erent sets of
DVs. - Multivariate Analysis. - Herv´ e Abdi, The University of Texas at Dallas -
Multivariate Analysis (Probability and Mathematical Statistics) (Paperback) by
Kanti V. Mardia, J. T. Kent , J. M. Bibby
Multivariate Statistical Analysis: A Conceptual Introduction by Sam Kash Kachigan
(Paperback - Jun 1991)
Multivariate Data Analysis (6th Edition) by Joseph F. Hair, Bill Black, Barry Babin, and
Rolph E. Anderson (Hardcover - Nov 7, 2005)
Methods of Multivariate Analysis (Wiley Series in Probability and Statistics) by Alvin C.
Rencher (Hardcover - Mar 7, 2002)
An Introduction to Multivariate Statistical Analysis (Wiley Series in Probability and
Statistics) by T. W. Anderson (Hardcover - Jul 25, 2003)
Applied Multivariate Statistical Analysis by Wolfgang Härdle and Leopold Simar (Paperback
- Sep 10, 2007)
Applied Multivariate Statistical Analysis (6th Edition) by Richard A. Johnson and Dean W.
Wichern (Hardcover - April 2, 2007)
Using Multivariate Statistics (5th Edition) by Barbara G. Tabachnick and Linda S. Fidell
(Hardcover - Mar 3, 2006)
Multivariate Data Analysis (7th Edition) by Joseph F. Hair, William C. Black, Barry J.
Babin, and Rolph E. Anderson (Hardcover - Feb 23, 2009)
Reading and Understanding Multivariate Statistics by Laurence G. Grimm and Paul R. Yarnold
(Paperback - Jan 1995)
An Introduction to Applied Multivariate Analysis by Tenko Raykov and George A. Marcoulides
(Hardcover - Mar 10, 2008)
Multivariate Statistical Methods: A Primer, Third Edition by Bryan F.J. Manly (Paperback -
Jun 30, 2004)
Applied Multivariate Analysis
Many research questions in the social and behavioral sciences are investigated using
statistical models. We offer a crash course in applied multivariate analysis in which we
focus on: multiple linear regression analysis (including the use of dummy variables),
logistic regression analysis, simple and factorial ANOVA, interaction effects, repeated
measures ANOVA, ANCOVA, MANOVA, MANCOVA, and exploratory factor analysis.
In this course there is a strong emphasis on how to perform these analyses using the
computer program SPSS, and how to interpret SPSS output in substantive terms.
SOCIAL BOND THEORY AND BINGE DRINKING AMONG COLLEGE
STUDENTS: A MULTIVARIATE ANALYSIS.
College Student Journal, September 1, 1999, DURKIN, KEITH F.; WOLFE, TIMOTHY W.; CLARK,
This paper presents the results of a research project that examined the influence of
social bond variables on binge drinking in a sample of college students. A questionnaire
containing items which reflected a number of social bond variables and a measure of
frequency of binge drinking was administered to a sample (n=247) of college students. The
results indicated that nearly all of the social bond measures were inversely related to
the frequency of binge drinking. A multivariate model that used these social bond measures
explained approximately one-quarter of the variance in ...