Modeling a Set of Variables with Different Attributes on a Quantitative Dependent Variable: An Application of Dichotomous Variables
This study outlines the methodology employed to model the relationship among a set of dichotomous variables, which represent attributes, on a nominal scale. The objective is to elucidate their influence on a quantitative dependent variable measured on a ratio scale. This approach allows for the quan...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-07-01
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| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/68/1/9 |
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| Summary: | This study outlines the methodology employed to model the relationship among a set of dichotomous variables, which represent attributes, on a nominal scale. The objective is to elucidate their influence on a quantitative dependent variable measured on a ratio scale. This approach allows for the quantification of the impact of these attributes and their significance in shaping the behavior of the entity possessing them. The resolution method employed for the estimation is ordinary least squares. However, it is crucial to note that interpreting the estimators in the resulting model requires a nuanced perspective, distinguishing it from the conventional interpretation of slope or rate of change in a classic model. To clarify, these estimators align with the average behavior of the dependent variable concerning binary characteristics, and the outcomes are consistent with the analysis of variance. |
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| ISSN: | 2673-4591 |