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Thanks

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- Thread starter Purgum
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- #1

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Thanks

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HallsofIvy

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I'm not sure what data you have but if you have P(t) for at least 3 different times for each patient, you can use the data to determine C, m, and n for each patient. Just put the values for t and P(t) into the equation and you will have three equations to solve for C, m, and n. If you have more than 3 "data points" for a patient, you can check how well those values correspond to P(t) calculated from the formula to see how good that model is. Of course, it would be interesting to see if m and n are at least approximately the same for the different patients.

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However, I think, the data given is incomplete. The rate should be dependent in some way on the number of tumour cells; for example, the growth rate proportional to the no of tumour cells and death rate constant. The question given as such does not seem logical.

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HallsofIvy

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That's exactly what I said!

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EnumaElish

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If you have lots of data, you can statistically estimate mHallsofIvy said:... I'm not sure what data you have but if you have P(t) for at least 3 different times for each patient, you can use the data to determine C, m, and n for each patient. ...

P

where b

or more generally:

P

where you can also test the expectation a

You need to check for serial autocorrelation; almost surely you will encounter positive autocorrelation (e.g. using Durbin-Watson test); if so, you'll need to correct for it.

You can also test whether m - n is identical across patients and/or over time for each patient, by building slightly more complicated regression equations.

Alternatively you may want to specify percentage growth rates (instead of linear as above).

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