Quantitative models in marketing research / Philip Hans Franses and Richard Paap.

Includes bibliographical references (p. 196-201) and index.

On marketing research -- Data -- Models -- Features of marketing research data -- Quantitative models -- Marketing performance measures -- A continuous variable -- A binomial variable -- An unordered multinomial variable -- An ordered multinomial variable -- A limited continuous variable -- A duration variable -- A continuous dependent variable -- The standard Linear Regression model -- Estimation -- Estimation by Ordinary Least Squares -- Estimation by Maximum Likelihood -- Diagnostics, model selection and forecasting -- Diagnostics -- Model selection -- Forecasting -- Modeling sales -- Advanced topics -- A binomial dependent variable -- Representation and interpretation -- Modeling a binomial dependent variable -- The Logit and Probit models -- Model interpretation -- Estimation -- The Logit model -- The Probit model -- Visualizing estimation results -- Diagnostics, model selection and forecasting -- Diagnostics -- Model selection -- Forecasting -- Modeling the choice between two brands -- Advanced topics -- Modeling unobserved heterogeneity -- Modeling dynamics -- Sample selection issues -- An unordered multinomial dependent variable -- Representation and interpretation -- The Multinomial and Conditional Logit models -- The Multinomial Probit model -- The Nested Logit model -- Estimation -- The Multinomial and Conditional Logit models -- The Multinomial Probit model -- The Nested Logit model -- Diagnostics, model selection and forecasting -- Diagnostics -- Model selection -- Forecasting.

"Recent advances in data collection and data storage techniques enable marketing researchers to study the characteristics of a large range of transactions and purchases, in particular the effects of household-specific characteristics and marketing-mix variables." "This book presents the most important and practically relevant quantitative models for marketing research. Each model is presented in detail with a self-contained discussion, which includes: a demonstration of the mechanics of the model, empirical analysis, real-world examples, and interpretation of results and findings. The reader of the book will learn how to apply the techniques, as well as understand the latest methodological developments in the academic literature." "Pathways are offered in the book for students and practitioners with differing statistical and mathematical skill levels, although a basic knowledge of elementary numerical techniques is assumed."--BOOK JACKET.