Modern Methods for Business Research

by George A. Marcoulides (Editor)

Overview

This volume introduces the latest popular methods for conducting business research. The goal of each chapter author—a leading authority in a particular subject area—is to provide an understanding of each method with a minimum of mathematical derivations. The chapters are organized within three general interrelated topics—Measurement, Decision Analysis, and Modeling.

The chapters on measurement discuss generalizability theory, latent trait and latent class models, and multi-faceted Rasch modeling. The chapters on decision analysis feature applied location theory models, data envelopment analysis, and heuristic search procedures. The chapters on modeling examine exploratory and confirmatory factor analysis, dynamic factor analysis, partial least squares and structural equation modeling, multilevel data analysis, modeling of longitudinal data by latent growth curve methods and structures, and configural models of longitudinal categorical data.

Product Details

ISBN-13:	9780805830934
Publisher:	Taylor & Francis
Publication date:	03/01/1998
Series:	Quantitative Methodology Series
Pages:	448
Product dimensions:	6.00(w) x 9.00(h) x (d)

Table of Contents

Contents: Preface. G.A. Marcoulides, Applied Generalizability Theory Models. K.M. Schmidt McCollam, Latent Trait and Latent Class Models. M.E. Lunz, J.M. Linacre, Measurement Designs Using Multifacet Rasch Modeling. Z. Drezner, T. Drezner, Applied Location Theory Models. A.C. Soteriou, S.A. Zenios, Data Envelopment Analysis: An Introduction and an Application to Bank Branch Performance Assessment. S. Salhi, Heuristic Search Methods. R.H. Heck, Factor Analysis: Exploratory and Confirmatory Approaches. S.L. Hershberger, Dynamic Factor Analysis. E.E. Ridgon, Structural Equation Modeling. W.W. Chin, The Partial Least Squares Approach for Structural Equation Modeling. D. Kaplan, Methods for Multilevel Data Analysis. J.J. McArdle, Modeling Longitudinal Data by Latent Growth Curve Methods. P.K. Wood, Structural and Configural Models for Longitudinal Categorical Data.