Nonparallel Regressions with Indicator Variables
- Timothy Gregoire
AbstractA multiple linear regression model which includes 0/1 variables to indicatemembership in a group is a convenient way to model parallel regression surfaces.Building upon this, an extended model which includes predictor variables thatare the product of the indicator and other variables willcoincide with separate regressions for each group using only the other predictors.The algebraic basis for this concurrence is demonstrated.Least squares estimation is presumed.Examples with two groups and with four groups are presented.
This work is licensed under a Creative Commons Attribution 4.0 License.
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