# What type of model makes sense?

I am looking to model physical activity (in minutes) as my dependent variable. I have several independent variables of the environment around the school (intersections, traffic, etc).

What type of model would make sense? I was thinking multiple linear regression but some of the variables do not really have a linear relationship.

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Could you tell us something about the evidence you have of nonlinear relationships? In many cases a little bit of nonlinearity won't matter. –  whuber Aug 22 '12 at 19:08

Linear regression can accommodate non-straight-line relationships between IVs and the DV through various transformations of variables, addition of polynomial terms and so on.

That is a model like

$y = b_0 + b_1x_1^2 + b_2x_1 + b_3x_3^5$

is a linear model. But a model such as

$y = b_0 + 2^{b_1x_1}$

is not.

If the data are really nonlinear, then the choice of model depends partly on what you know about the relationships. If you don't know much, a spline regression may work well.

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I have tried to create log's for the IV but there is still no linear relationship, is there another way to transform the variables. Findings to date on the relationships between these variables is quite mixed. I will look into a spline regression. Thanks –  user10720 Aug 22 '12 at 18:29
Have you looked into Box-Cox? It's been discussed here a lot, and there are also lots of resources on the web. –  Peter Flom Aug 22 '12 at 18:36
Nope I will look into Box-Cox thanks. –  user10720 Aug 22 '12 at 18:40