Prediction analysis of cross classifications /

By:

Hildebrand, David K

Contributor(s):

Material type: Text

TextPublication details: New York : Wiley, c1977.Description: xv, 311 p. :illISBN:

0471395757

Subject(s):

Prediction theory

DDC classification:

519.5'4 HIL

LOC classification:

QA279.2 .H54

Summary: Without acknowledging the paradigm difference between testing theory and predicting events, researchers in the field of management and organization continue to use the DEL-technique as a promising technique to evaluate theory based on cross-classification data analysis. We address the purpose and interpretation of the DEL-measure within the theory-testing and events-predicting paradigm. We argue that DEL, a proportionate reduction in error measure, is not to be interpreted in terms of the proportionate error reduction of knowing a prediction rule over not knowing it. In addition, a significant DEL-value is not to be interpreted as a dependence-measure of acceptance of a hypothesis as the only and best relationship between two categorical variables, just as a non-significant DEL-value cannot be interpreted as a measure of independence. Furthermore, an alternative proportionate reduction in error measure generates unequivocally interpretable results compared to the DEL-technique.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Monograph & others	CBN HQ Library General Stacks	Non-fiction	519.5'4 HIL (Browse shelf(Opens below))	Available		31008100021530

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Previous	519.5'4 AIT Statistical Prediction Analysis /	519.5'4 CHA Applied statistics in decision-making /	519.5'4 FOR Forecasting :	519.5'4 HIL Prediction analysis of cross classifications /	519.5'4 STA Statistical inference in continuous time economic models /	519.5'4 USE The Uses and abuses of forecasting /	519.5'42 LEO Bayesian methods :	Next

Includes indexes.

Bibliography: p. 294-299.

Without acknowledging the paradigm difference between testing theory and predicting events, researchers in the field of management and organization continue to use the DEL-technique as a promising technique to evaluate theory based on cross-classification data analysis. We address the purpose and interpretation of the DEL-measure within the theory-testing and events-predicting paradigm. We argue that DEL, a proportionate reduction in error measure, is not to be interpreted in terms of the proportionate error reduction of knowing a prediction rule over not knowing it. In addition, a significant DEL-value is not to be interpreted as a dependence-measure of acceptance of a hypothesis as the only and best relationship between two categorical variables, just as a non-significant DEL-value cannot be interpreted as a measure of independence. Furthermore, an alternative proportionate reduction in error measure generates unequivocally interpretable results compared to the DEL-technique.

aia 26/09/17

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