Moutinho / Hutcheson The SAGE Dictionary of Quantitative Management Research

1. 1. Auflage 2011
ISBN: 978-1-4462-4582-8
Verlag: SAGE Publications
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 344 Seiten, EPUB

A must-have reference resource for quantitative management researchers, the Dictionary contains over 100 entries covering the fundamentals of quantitative methodologies; covering both analysis and implementation and examples of use, as well as detailed graphics to aid understanding.
Every entry features:
-An introduction to the topic,
-Key relevant features,
-A worked example,
-A concise summary and a selection of further reading suggestions
-Cross-references to associated concepts within the dictionary

Autoren/Hrsg.

Moutinho, Luiz A M

Moutinho, Luiz

Hutcheson, Graeme D

Inhaltsverzeichnis

Introduction

A/B Split Testing

Analytic Hierarchy Process

Association and Causation in Quantitative Research

Association Rule Mining

Bass Model

Canonical Correlation

Chaos Theory

Classification and Ranking Belief Simplex

Clustering Algorithms

Cluster Analysis

Coding Conventions for Representing Information

Conceptual Equivalence

Confidence Intervals

Conjoint Analysis

Construct Operationalization Review (CORE)

Correlation Analysis

Correspondence Analysis

Cross-National/Cultural Comparisons

Cross-Sectional Designs

Data Envelopment Analysis in Management

Data Mining

Data Set Structure

Data Transformation

Dempster-Shafer Theory

Designing Experiments

Discriminant Analysis

Dominance Analysis

DS/AHP

Dummy Variable Coding

Event Studies Methodology

Evaluation Research

Experimental Design

Exploratory or Confirmatory Factor Analysis

Factor Analysis

Fuzzy Decision Trees

Fuzzy Sets

Fuzzy Time Series Models

Generalized Linear Mixed Models

Generalized Linear Models

Geodemographics

Geographical Information Systems

Growth Models

Intraclass Correlation Coefficient

Internal and External Validity

Item Response Theory

Item Response Theory for Management

Latent Segments Analysis

Latent Variable Models

Logical Discriminant Models

Logistic Growth Model

Logistic Regression

Logistic Spline Model

Measurement Reliability

Measurement Invariance in Multigroup Research

Measurement Scales

Moderator-Mediator Variable Distinction

Mixture Models

Multi-Attribute Utility/Value Theory

Multidimensional Scaling

Multilevel Models

Multi-Logistic Growth Model

Multinomial Logistic Regression

Multi-State Modelling

Non-Parametric Measures of Association

Optimal Control Models in Management

Ordinary Least-Squares Regression

Panel Design

Paper Versus Electronic Surveys

Parametric Tests

Partial Correlation

Principal Components Analysis

Programme Evaluation

PROMETHEE Method of Ranking Alternatives

Proportional Odds Model

Quantile Estimators

Quantile Estimators - Bootstrap Confidence Intervals

Rasch Model for Measurement

Receiver Operating Characteristic

Response Styles in Cross-National Research

Retail Site Selection

Sampling Equivalence in Cross-National Research

Sample Size for Proportions

Sample Sizes Versus Usable Observations

Self-Organizing Maps

Single-Case Research Designs

Single-Case Single-Baseline Designs

Sngle-Case Multiple-Baseline Designs

Simulation - Discrete Event

Simulation - Methodology

Structural Equation Modelling in Business Management

Structural Equation Modelling in Marketing - Part 1: Introduction and Basic Concepts

Structural Equation Modelling in Marketing - Part 2: Model Calibration

Structural Equation Modelling in Marketing - Part 3: An Example

Study Design

Survey Design

Tabu Search

Testing a Simple Hypothesis

Validity

Variable Precision Rough Sets

Voronoi Diagrams

Web Surveys

Index

Über Autor(innen)

Hutcheson, Graeme D
Dr Graeme Hutcheson specialises in the application of statistical models in social science research. He has published widely in management and education, mostly with respect to the use and interpretation of generalized regression models.

Moutinho, Luiz A M
Luiz Moutinhois Foundation Chair of Marketing at the Department of Management, University of Glasgow