Hallo all, I have a problem in a glm model. The glm model has, among the other variables, 4 dummy variables: flg.a2 (takes values 0 or 1) flg.d.na2 (takes values 0 or 1) flg.v2 (takes values 0 or 1) flg.cc2 (takes values 0 or 1) In addition to these variables, I have included their interaction, with the order: (flg.a2+flg.d.na2+flg.v2+flg.cc2)^2 In the model?s summary there are not some interactions (flg.a2:flg.cc2 e flg.d.na2:flg.cc2), because there are not cases that present these interactions. Then, the model?s summary shows that the p-value of the interaction flg.a2:flg.d.na2 is 0.66, and so this interaction can be eliminated. But when I apply the test anova between the model whit this interaction and the model without this interaction, the p-value is 0.004, and so, the interaction is significative. Why I obtain this difference? Many thanks for any help, Simona