Hello? Does anyone know how I can implement the below equation in R? I would like to estimate the following equation:
y=beta_ij * (1+gamma_j * dummy) * x_ij where y is continuous, and all the x variables (j of them) are i=3 level categorical variables. The intuition is that instead of estimating the additive value for a dummy variable, I would like to estimate the multiplicative value for the dummy variable. Thus the presence of the dummy would scale the beta. Note that for each x variable there is only one gamma. For concreteness, you can imagine that y is a continious test score, x are categorical variables indicating different types of education achievements, each type of education achievement is categorised in 3 levels (none, some, a lot), and the dummy indicates race. In this model I believe that race affects test scores proportionally to estimated beta of each education level. This avoids having to estimate a gamma for each education achievement level. Is the solution to simply use nls {stats} and type out the equation? Hope the explanation makes sense, happy to explain further. Best wishes, Peter ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.