Quantitative Models in Marketing Research / Philip Hans Franses, Richard Paap.

Format:

Book

Contributor:

Franses, Philip Hans, 1963-

Paap, Richard, 1969-

Series:

Cambridge books online.

Language:

English

Subjects (All):

Marketing research--Mathematical models.

Marketing research.

Physical Description:

1 online resource (224 pages) : digital, PDF file(s)

Place of Publication:

Cambridge : Cambridge University Press, 2001.

System Details:

Mode of access: World Wide Web.

text file

PDF

Summary:

Presents the most important and practically relevant quantitative models used for marketing research.

Contents:

1.1.1 On marketing research 2

1.1.2 Data 4

1.1.3 Models 5

2 Features of marketing research data 10

2.1 Quantitative models 10

2.2 Marketing performance measures 12

2.2.1 A continuous variable 13

2.2.2 A binomial variable 15

2.2.3 An unordered multinomial variable 18

2.2.4 An ordered multinomial variable 19

2.2.5 A limited continuous variable 21

2.2.6 A duration variable 24

3 A continuous dependent variable 29

3.1 The standard Linear Regression model 29

3.2 Estimation 34

3.2.1 Estimation by Ordinary Least Squares 34

3.2.2 Estimation by Maximum Likelihood 35

3.3 Diagnostics, model selection and forecasting 38

3.3.1 Diagnostics 39

3.3.2 Model selection 41

3.3.3 Forecasting 43

3.4 Modeling sales 44

3.5 Advanced topics 47

4 A binomial dependent variable 49

4.1 Representation and interpretation 49

4.1.1 Modeling a binomial dependent variable 50

4.1.2 The Logit and Probit models 53

4.1.3 Model interpretation 55

4.2 Estimation 58

4.2.1 The Logit model 59

4.2.2 The Probit model 60

4.2.3 Visualizing estimation results 61

4.3 Diagnostics, model selection and forecasting 61

4.3.1 Diagnostics 62

4.3.2 Model selection 63

4.3.3 Forecasting 65

4.4 Modeling the choice between two brands 66

4.5 Advanced topics 71

4.5.1 Modeling unobserved heterogeneity 71

4.5.2 Modeling dynamics 73

4.5.3 Sample selection issues 73

5 An unordered multinomial dependent variable 76

5.1 Representation and interpretation 77

5.1.1 The Multinomial and Conditional Logit models 77

5.1.2 The Multinomial Probit model 86

5.1.3 The Nested Logit model 88

5.2 Estimation 91

5.2.1 The Multinomial and Conditional Logit models 92

5.2.2 The Multinomial Probit model 95

5.2.3 The Nested Logit model 95

5.3 Diagnostics, model selection and forecasting 96

5.3.1 Diagnostics 96

5.3.2 Model selection 97

5.3.3 Forecasting 99

5.4 Modeling the choice between four brands 101

5.5 Advanced topics 107

5.5.1 Modeling unobserved heterogeneity 107

5.5.2 Modeling dynamics 108

5.A EViews Code 109

5.A.1 The Multinomial Logit model 110

5.A.2 The Conditional Logit model 110

5.A.3 The Nested Logit model 111

6 An ordered multinomial dependent variable 112

6.1 Representation and interpretation 113

6.1.1 Modeling an ordered dependent variable 113

6.1.2 The Ordered Logit and Ordered Probit models 116

6.1.3 Model interpretation 117

6.2 Estimation 118

6.2.1 A general ordered regression model 118

6.2.2 The Ordered Logit and Probit models 121

6.2.3 Visualizing estimation results 122

6.3 Diagnostics, model selection and forecasting 122

6.3.1 Diagnostics 123

6.3.2 Model selection 124

6.3.3 Forecasting 125

6.4 Modeling risk profiles of individuals 125

6.5 Advanced topics 129

6.5.1 Related models for an ordered variable 130

6.5.2 Selective sampling 130

7 A limited dependent variable 133

7.1 Representation and interpretation 134

7.1.1 Truncated Regression model 134

7.1.2 Censored Regression model 137

7.2 Estimation 142

7.2.1 Truncated Regression model 142

7.2.2 Censored Regression model 144

7.3 Diagnostics, model selection and forecasting 147

7.3.1 Diagnostics 147

7.3.2 Model selection 149

7.3.3 Forecasting 150

7.4 Modeling donations to charity 151

7.5 Advanced Topics 155

8 A duration dependent variable 158

8.1 Representation and interpretation 159

8.1.1 Accelerated Lifetime model 165

8.1.2 Proportional Hazard model 166

8.2 Estimation 168

8.2.1 Accelerated Lifetime model 169

8.2.2 Proportional Hazard model 170

8.3 Diagnostics, model selection and forecasting 172

8.3.1 Diagnostics 172

8.3.2 Model selection 174

8.3.3 Forecasting 175

8.4 Modeling interpurchase times 175

8.5 Advanced topics 179

8.A EViews code 182

8.A.1 Accelerated Lifetime model (Weibull distribution) 182

8.A.2 Proportional Hazard model (loglogistic distribution) 183

A.1 Overview of matrix algebra 184

A.2 Overview of distributions 187

A.3 Critical values 193.

Notes:

Title from publishers bibliographic system (viewed on 02 Mar 2012).

Other Format:

Print version:

ISBN:

9780511753794

9780521801669

Access Restriction:

Restricted for use by site license.