A Latent Look at Empirical Generalizations
All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, "model" $$\hbox{Observed Value} = \hbox{True Score} + \hbox{Error}$$ as a lens for better viewing empirical studies in search of empirical generalization...
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| Published in | Marketing science (Providence, R.I.) Vol. 14; no. 3_supplement; pp. G61 - G70 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Linthicum
INFORMS
01.08.1995
Institute for Operations Research and the Management Sciences |
| Series | Marketing Science |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0732-2399 1526-548X |
| DOI | 10.1287/mksc.14.3.G61 |
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| Abstract | All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, "model"
$$\hbox{Observed Value} = \hbox{True Score} + \hbox{Error}$$
as a lens for better viewing empirical studies in search of empirical generalizations in marketing. This lens is especially valuable when the unit of analysis is the individual consumer. However, even when a macro study contrasts price elasticities across cities, this
O = T + E
framework can be very helpful. |
|---|---|
| AbstractList | All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, “model” $$\hbox{Observed Value} = \hbox{True Score} + \hbox{Error}$$ as a lens for better viewing empirical studies in search of empirical generalizations in marketing. This lens is especially valuable when the unit of analysis is the individual consumer. However, even when a macro study contrasts price elasticities across cities, this framework can be very helpful. All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, "model" Observed Value = True Score + Error as a lens for better viewing empirical studies in search of empirical generalizations in marketing. This lens is especially valuable when the unit of analysis is the individual consumer. However, even when a macro study contrasts price elasticities across cities, this O = T + E framework can be very helpful. All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, "model" $$\hbox{Observed Value} = \hbox{True Score} + \hbox{Error}$$ as a lens for better viewing empirical studies in search of empirical generalizations in marketing. This lens is especially valuable when the unit of analysis is the individual consumer. However, even when a macro study contrasts price elasticities across cities, this O = T + E framework can be very helpful. All empirical data and the resulting parameters are subject to error. A lens for better viewing empirical studies in search of empirical generalizations in marketing is presented: Observed Value = True Score + Error. This lens is especially valuable when the unit of analysis is the individual consumer. However, even when a macro study contrasts price elasticities across cities, this O = T + E framework can be very helpful. All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, “model” [Formula: see text] as a lens for better viewing empirical studies in search of empirical generalizations in marketing. This lens is especially valuable when the unit of analysis is the individual consumer. However, even when a macro study contrasts price elasticities across cities, this O = T + E framework can be very helpful. |
| Author | Morrison, Donald G. Silva-Risso, Jorge |
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| DOI | 10.1287/mksc.14.3.G61 |
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| Snippet | All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, "model"... All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, "model" Observed Value... All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, “model” [Formula: see... All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, “model”... All empirical data and the resulting parameters are subject to error. A lens for better viewing empirical studies in search of empirical generalizations in... |
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| SubjectTerms | appropriate comparisons Brand preferences Brands Consumer behavior Consumers Estimators Generalizations Households Marketing Marketing mixes Mathematical models Maximum likelihood estimation Price elasticity Probability distribution Purchasing Science shrinkage estimators Standard error Statistical analysis Statistical data Statistical variance Stochastic Choice Phenomena summary statistics unobservable constructs Unobservables Variance |
| Title | A Latent Look at Empirical Generalizations |
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