search for: x1q

...bles, each being a factor: df <- expand.grid(X1=c("p","q"), X2=c("A","B","C")) print(model.matrix(~(X1+X2)^2 ,data=df)) print(model.matrix(~(X1+X2)^2 -X1,data=df)) print(model.matrix(~(X1+X2)^2 -X2,data=df)) The result is: (Intercept) X1q X2B X2C X1q:X2B X1q:X2C 1 1 0 0 0 0 0 2 1 1 0 0 0 0 3 1 0 1 0 0 0 4 1 1 1 0 1 0 5 1 0 0 1 0 0 6 1 1 0 1 0 1 (Intercept) X2B X2C...

Hi, I recently ran into an inconsistency in the way model.matrix.default handles factor encoding for higher level interactions with categorical variables when the full hierarchy of effects is not present. Depending on which lower level interactions are specified, the factor encoding changes for a higher level interaction. Consider the following minimal reproducible example: -------------- >

...p","q"), X2=c("A","B","C")) >> print(model.matrix(~(X1+X2)^2 ,data=df)) >> print(model.matrix(~(X1+X2)^2 -X1,data=df)) >> print(model.matrix(~(X1+X2)^2 -X2,data=df)) >> >> The result is: >> >> (Intercept) X1q X2B X2C X1q:X2B X1q:X2C >> 1 1 0 0 0 0 0 >> 2 1 1 0 0 0 0 >> 3 1 0 1 0 0 0 >> 4 1 1 1 0 1 0 >> 5 1 0 0 1 0 0 >> 6...

...C")) >> >> print(model.matrix(~(X1+X2)^2 ,data=df)) >> >> print(model.matrix(~(X1+X2)^2 -X1,data=df)) >> >> print(model.matrix(~(X1+X2)^2 -X2,data=df)) >> >> >> >> The result is: >> >> >> >> (Intercept) X1q X2B X2C X1q:X2B X1q:X2C >> >> 1 1 0 0 0 0 0 >> >> 2 1 1 0 0 0 0 >> >> 3 1 0 1 0 0 0 >> >> 4 1 1 1 0 1 0 >> >> 5 1 0...

...2)^2 ,data=df)) >> >> >> print(model.matrix(~(X1+X2)^2 -X1,data=df)) >> >> >> print(model.matrix(~(X1+X2)^2 -X2,data=df)) >> >> >> >> >> >> The result is: >> >> >> >> >> >> (Intercept) X1q X2B X2C X1q:X2B X1q:X2C >> >> >> 1 1 0 0 0 0 0 >> >> >> 2 1 1 0 0 0 0 >> >> >> 3 1 0 1 0 0 0 >> >> >> 4 1 1 1 0 1 0...

...A","B","C")) > >> print(model.matrix(~(X1+X2)^2 ,data=df)) > >> print(model.matrix(~(X1+X2)^2 -X1,data=df)) > >> print(model.matrix(~(X1+X2)^2 -X2,data=df)) > >> > >> The result is: > >> > >> (Intercept) X1q X2B X2C X1q:X2B X1q:X2C > >> 1 1 0 0 0 0 0 > >> 2 1 1 0 0 0 0 > >> 3 1 0 1 0 0 0 > >> 4 1 1 1 0 1 0 > >> 5 1 0 0 1 0...

...print(model.matrix(~(X1+X2)^2 -X1,data=df)) >> >> >> >> print(model.matrix(~(X1+X2)^2 -X2,data=df)) >> >> >> >> >> >> >> >> The result is: >> >> >> >> >> >> >> >> (Intercept) X1q X2B X2C X1q:X2B X1q:X2C >> >> >> >> 1 1 0 0 0 0 0 >> >> >> >> 2 1 1 0 0 0 0 >> >> >> >> 3 1 0 1 0 0 0 >> >> >> >> 4...

...rint(model.matrix(~(X1+X2)^2 ,data=df)) > >> >> print(model.matrix(~(X1+X2)^2 -X1,data=df)) > >> >> print(model.matrix(~(X1+X2)^2 -X2,data=df)) > >> >> > >> >> The result is: > >> >> > >> >> (Intercept) X1q X2B X2C X1q:X2B X1q:X2C > >> >> 1 1 0 0 0 0 0 > >> >> 2 1 1 0 0 0 0 > >> >> 3 1 0 1 0 0 0 > >> >> 4 1 1 1 0 1 0 > >> &...

...t; >> >> print(model.matrix(~(X1+X2)^2 -X1,data=df)) > >> >> >> print(model.matrix(~(X1+X2)^2 -X2,data=df)) > >> >> >> > >> >> >> The result is: > >> >> >> > >> >> >> (Intercept) X1q X2B X2C X1q:X2B X1q:X2C > >> >> >> 1 1 0 0 0 0 0 > >> >> >> 2 1 1 0 0 0 0 > >> >> >> 3 1 0 1 0 0 0 > >> >> >> 4 1 1 1...

...+X2)^2 -X1,data=df)) > >> >> >> >> print(model.matrix(~(X1+X2)^2 -X2,data=df)) > >> >> >> >> > >> >> >> >> The result is: > >> >> >> >> > >> >> >> >> (Intercept) X1q X2B X2C X1q:X2B X1q:X2C > >> >> >> >> 1 1 0 0 0 0 0 > >> >> >> >> 2 1 1 0 0 0 0 > >> >> >> >> 3 1 0 1 0 0 0 > >> >> &gt...