Kooperativer Bibliotheksverbund

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Format: 1 online resource (xiii, 206 pages) : , digital, PDF file(s).

Edition: 1st ed.

ISBN: 1-107-12279-1 , 0-521-14365-9 , 0-511-11936-4 , 0-511-15345-7 , 0-511-30344-0 , 1-280-15484-5 , 0-511-04764-9 , 0-511-75379-9

Content: Advances in data collection and data storage techniques have enabled marketing researchers to study the individual characteristics of a large range of transactions and purchases, in particular the effects of household-specific characteristics. This 2001 book presents 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 methodological developments in the academic literature. Pathways are offered in the book for students and practitioners with differing numerical skill levels; a basic knowledge of elementary numerical techniques is assumed.

Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015). , 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. , English

Additional Edition: ISBN 0-521-80166-4

Additional Edition: ISBN 0-511-01301-9

Language: English

URL: https://doi.org/10.1017/CBO9780511753794

UID:

Format: 1 online resource (222 pages)

Edition: 1st ed.

ISBN: 9780521801669 , 9780511153457

Content: This 2001 book presents important and practically relevant quantitative models used 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

Note: Cover -- Half-title -- Title -- Copyright -- Contents -- Figures -- Tables -- Preface -- 1 Introduction and outline of the book -- 1.1 Introduction -- 1.1.1 On marketing research -- 1.1.2 Data -- 1.1.3 Models -- 1.2 Outline of the book -- 1.2.1 How to use this book -- 1.2.2 Outline of chapter contents -- 2 Features of marketing research data -- 2.1 Quantitative models -- 2.2 Marketing performance measures -- 2.2.1 A continuous variable -- 2.2.2 A binomial variable -- 2.2.3 An unordered multinomial variable -- 2.2.4 An ordered multinomial variable -- 2.2.5 A limited continuous variable -- 2.2.6 A duration variable -- 2.2.7 Summary -- 2.3 What do we exclude from this book? -- 3 A continuous dependent variable -- 3.1 The standard Linear Regression model -- 3.2 Estimation -- 3.2.1 Estimation by Ordinary Least Squares -- 3.2.2 Estimation by Maximum Likelihood -- 3.3 Diagnostics, model selection and forecasting -- 3.3.1 Diagnostics -- 3.3.2 Model selection -- 3.3.3 Forecasting -- 3.4 Modeling sales -- 3.5 Advanced topics -- 4 A binomial dependent variable -- 4.1 Representation and interpretation -- 4.1.1 Modeling a binomial dependent variable -- 4.1.2 The Logit and Probit models -- 4.1.3 Model interpretation -- 4.2 Estimation -- 4.2.1 The Logit model -- 4.2.2 The Probit model -- 4.2.3 Visualizing estimation results -- 4.3 Diagnostics, model selection and forecasting -- 4.3.1 Diagnostics -- 4.3.2 Model selection -- 4.3.3 Forecasting -- 4.4 Modeling the choice between two brands -- 4.5 Advanced topics -- 4.5.1 Modeling unobserved heterogeneity -- 4.5.2 Modeling dynamics -- 4.5.3 Sample selection issues -- 5 An unordered multinomial dependent variable -- 5.1 Representation and interpretation -- 5.1.1 The Multinomial and Conditional Logit models -- The Multinomial Logit model -- The Conditional Logit model -- A general logit specification , 8 A duration dependent variable -- 8.1 Representation and interpretation -- 8.1.1 Accelerated Lifetime model -- 8.1.2 Proportional Hazard model -- 8.2 Estimation -- 8.2.1 Accelerated Lifetime model -- 8.2.2 Proportional Hazard model -- 8.3 Diagnostics, model selection and forecasting -- 8.3.1 Diagnostics -- 8.3.2 Model selection -- 8.3.3 Forecasting -- 8.4 Modeling interpurchase times -- 8.5 Advanced topics -- Accelerated Lifetime model -- Proportional Hazard model -- 8.A EViews code -- 8.A.1 Accelerated Lifetime model (Weibull distribution) -- 8.A.2 Proportional Hazard model (loglogistic distribution) -- Appendix -- A.1 Overview of matrix algebra -- A.2 Overview of distributions -- A.3 Critical values -- Bibliography -- Author index -- Subject index , The independence of irrelevant alternatives -- 5.1.2 The Multinomial Probit model -- 5.1.3 The Nested Logit model -- 5.2 Estimation -- 5.2.1 The Multinomial and Conditional Logit models -- 5.2.2 The Multinomial Probit model -- 5.2.3 The Nested Logit model -- 5.3 Diagnostics, model selection and forecasting -- 5.3.1 Diagnostics -- 5.3.2 Model selection -- 5.3.3 Forecasting -- 5.4 Modeling the choice between four brands -- 5.5 Advanced topics -- 5.5.1 Modeling unobserved heterogeneity -- 5.5.2 Modeling dynamics -- 5.A. EViews Code -- 5.A.1 The Multinomial Logit model -- 5.A.2 The Conditional Logit model -- 5.A.3 The Nested Logit model -- 6 An ordered multinomial dependent variable -- 6.1 Representation and interpretation -- 6.1.1 Modeling an ordered dependent variable -- 6.1.2 The Ordered Logit and Ordered Probit models -- 6.1.3 Model interpretation -- 6.2 Estimation -- 6.2.1 A general ordered regression model -- 6.2.2 The Ordered Logit and Probit models -- 6.2.3 Visualizing estimation results -- 6.3 Diagnostics, model selection and forecasting -- 6.3.1 Diagnostics -- 6.3.2 Model selection -- 6.3.3 Forecasting -- 6.4 Modeling risk profiles of individuals -- 6.5 Advanced topics -- 6.5.1 Related models for an ordered variable -- 6.5.2 Selective sampling -- 7 A limited dependent variable -- 7.1 Representation and interpretation -- 7.1.1 Truncated Regression model -- 7.1.2 Censored Regression model -- Type-1 Tobit model -- Type-2 Tobit model -- 7.2 Estimation -- 7.2.1 Truncated Regression model -- 7.2.2 Censored Regression model -- Type-1 Tobit -- Type-2 Tobit -- 7.3 Diagnostics, model selection and forecasting -- 7.3.1 Diagnostics -- Residuals -- Specification tests -- 7.3.2 Model selection -- 7.3.3 Forecasting -- Truncated Regression model -- Censored Regression model -- 7.4 Modeling donations to charity -- 7.5 Advanced topics

Additional Edition: Print version Franses, Philip Hans Quantitative Models in Marketing Research Cambridge : Cambridge University Press,c2001 ISBN 9780521801669

Language: English

Keywords: Electronic books

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