You only have one response variable, so MANOVA is not appropriate. One option would be to compare BP ~ Weight + Height with BP ~ 1. That would give you a joint test of weight and height together. Since they are collinear, that should tell you the overall effect of "size". There are other options, most of which involve discarding some of the data. Frank Harrell's book is a font of wisdom on this sort of thing. Harrell, F. E., Jr. (2001). Regression Modeling Strategies. Springer. Simon.
On Thu, 2009-03-12 at 00:20 -0600, Ding Xiao wrote:
Hi All, I have questions about MANOVA which I am still not sure if appropriately I should use it. For example I have a data set like this: BloodPressure (BP) Weight Height 120 115 165 125 145 198 156 99 176 I know that BloodPressure is correlated with both Weight and Height, however colinearity exists between Weight and Height. When I use BP = Weight + Height as the model, one is got to be insignificant. I was trying to use a BP + Weight = Height model, but not sure how to use it. Should I use MANOVA? or I just have to do two equations as BP = Weight & Weight = Height Any suggestions and answers are greatly appreciated! Ding [[alternative HTML version deleted]]
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