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| Author: | Eakin, M. Schkader, L. L. Whiteside, M. |
| Title: | Optimal cost sampling for decision making with multiple regression models. |
| Journal: | Decision Sciences
1989 : WINTER, VOL. 20:1, p. 14-26 |
| Index terms: | LINEAR MODELS STATISTICAL METHODS DECISION THEORY |
| Language: | eng |
| Abstract: | An explicit relationship between sample size,sampling error and related costs is developed for the application of multiple regression models in observational studies. The authors provide graphs and formulas for determining the optimal sample sizes and related factors, in order to facilitate the application of the derived models. The major result is the following: the relative change in the total cost function is small if n is larger than twenty. A model-utility approach, however, may impose a lower bound on sample size. |
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