On the Analysis of Qualitative Data in Marketing Research

1977 ◽  
Vol 14 (1) ◽  
pp. 52-59 ◽  
Author(s):  
Paul E. Green ◽  
Frank J. Carmone ◽  
David P. Wachspress
Keyword(s):  
Categorical Data ◽  
Qualitative Data ◽  
Linear Models ◽  
Marketing Research ◽  
New Techniques ◽  
Consumer Adoption ◽  
Market Areas ◽  
Log Linear ◽  
Probability Of Adoption

Logit and log-linear models are new techniques for analyzing categorical data. Each of these models is described and applied to a problem involving consumer adoption of a new telecommunications service. The models provide probability-of-adoption predictions that can be used to select favorable market areas for promoting the service.

A Marketer'S Guide to Log-Linear Models for Qualitative Data Analysis

1980 ◽  
Vol 44 (3) ◽  
pp. 40-51 ◽  
Author(s):  
Wayne S. DeSarbo ◽  
David K. Hildebrand
Keyword(s):  
Data Analysis ◽  
Qualitative Data ◽  
Potential Problem ◽  
Linear Models ◽  
Model Fitting ◽  
Qualitative Data Analysis ◽  
Chi Square ◽  
Stepwise Procedures ◽  
Log Linear

This article presents a brief description of the development and use of log-linear models. Current research in areas of screening effects, partitioning chi-square statistics, stepwise procedures, and model fitting and selection is discussed. An analysis of inherent model ambiguities is provided, identifying potential problem areas for marketing applications.

Applying Log-Linear Models in Educational Research

1988 ◽  
Vol 32 (1) ◽  
pp. 3-24 ◽  
Author(s):  
John J. Kennedy
Keyword(s):  
Educational Research ◽  
Analysis Of Variance ◽  
Logit Model ◽  
Contingency Table ◽  
Goodness Of Fit ◽  
Qualitative Data ◽  
Linear Models ◽  
Linear Modelling ◽  
Acceptable Model ◽  
Log Linear

This didactic illustrates the Goodman-Kennedy approach to log-linear modelling within the context of two educational research examples. The first example lends itself to a symmetrical analysis. To qualitative data presented within a 2 × 2 × 2 contingency table, general log-linear models are specified and assessed for goodness of fit. Subsequently an acceptable model is identified and interpreted. In a second example, an asymmetrical logit-model analysis is performed on data in a 2 × 2 × 5 table. It is shown that a subset of general models can be fitted to observed data and that resultant component chi-squares can be used to assess logit response in a manner that is analogous to the analysis of variance.

An Assessment of the Contribution of Log Linear Models to Marketing Research

1981 ◽  
Vol 45 (2) ◽  
pp. 89 ◽  
Author(s):  
Robert C. Blattberg ◽  
Robert J. Dolan
Keyword(s):  
Linear Models ◽  
Marketing Research ◽  
Log Linear

Log-Linear, Logit-Linear Models: A Didactic

1981 ◽  
Vol 6 (1) ◽  
pp. 75-102 ◽  
Author(s):  
Frank B. Baker
Keyword(s):  
Linear Model ◽  
Educational Research ◽  
Qualitative Data ◽  
Linear Models ◽  
Contingency Tables ◽  
Basic Logic ◽  
Data Analyses ◽  
Potential Applications ◽  
Log Linear ◽  
Model Technique

The recently developed log-linear model technique for the analysis of contingency tables has many potential applications within educational research. This paper describes the two major models, log-linear and logit-linear, that are employed under this approach. The basic logic of each is developed and illustrative data analyses presented. In addition, the underlying communality of the two schemes is shown. The intent was to provide the reader with perspective that will facilitate understanding the approach and its application to the analysis of qualitative data.

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