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03-11-2011 12:41 PM

Hi,

I have soil nutrients dataset from three years recieving different levels of treatments. My interest is to know whether there was any significant change occured over the time or not. So, basically I want to measure the change occured at the end of first year vs at the end of third year.

My question is do we need to set up my dependent variable as change measured or I can simply run it as a repeated measures to observed the change.

Thanks

Bhupinder

I have soil nutrients dataset from three years recieving different levels of treatments. My interest is to know whether there was any significant change occured over the time or not. So, basically I want to measure the change occured at the end of first year vs at the end of third year.

My question is do we need to set up my dependent variable as change measured or I can simply run it as a repeated measures to observed the change.

Thanks

Bhupinder

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Posted in reply to Bhupinder

03-11-2011 01:34 PM

Those are two ways to attack it. They involve different assumptions, so there is no uniformly "best" way.

There is a third way, and that is to include all three time points in a GLM as dependent variables. Yet different assumptions. However, it allows you to explicitly test if the change over time is linear or not (using orthogonal polynomials).

There is a third way, and that is to include all three time points in a GLM as dependent variables. Yet different assumptions. However, it allows you to explicitly test if the change over time is linear or not (using orthogonal polynomials).

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Posted in reply to Doc_Duke

03-11-2011 03:34 PM

I have few random parameters so have to use MIXED model. The other things is that it is not possible to compare the data from second year due to some restrictions. So, basically, I have only two years data (2007 and 2009). Do I need to set it up as repeated measures or can use them both as dependent variables?

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Posted in reply to Bhupinder

03-11-2011 02:05 PM