Changing sign of data (regression)

This is a common method used in MRI experiments where the signal is flipped to avoid negative values. In summary, there may be instances where flipping the signs of data points is necessary in order to correctly model an exponential function, such as in MRI experiments where the absolute values of magnetisation are being measured. This approach may be used to avoid negative values and obtain an accurate measurement of the underlying quantity.
  • #1
roam
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Homework Statement



I was trying to fit experimental data which are theoretically modeled by an exponential function. They are shown in the first graph below. For the first set (red line), the data does not appear to be exponential. My lecturer once said that I need to flip the signs of the first few data points to get an exponential (see the second plot).

431qBiJ.png


Is there any justification for doing this? Are there any situations where such a thing would be appropriate?

This data relate to the absolute values of magnetisation in an MRI experiment.

Homework Equations


3. The Attempt at a Solution [/B]

When I flipped the signs of the first six data points, I got a curve which could then be modeled with an exponential, just like the other data sets. I got R2 = 0.99971, and the time constant I calculated from this was in agreement with the expected value.

So, why does this method work? Could there be any justification for doing this?

Any help would be greatly appreciated.
 
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  • #2
Without knowing what your experimental setup is and what exactly is it that you are fitting to, we can't really tell with certainty. However, my suspicion is that your experimental device is only able to measure the absolute value of the quantity (or its square, since I see intensity in your graph there), which is why you have to "reverse" the sign to recover the actual value of the quantity possessed by the system.
 
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1. What is the meaning of changing sign of data in regression analysis?

In regression analysis, changing sign of data refers to the change in direction of the relationship between two variables. This means that a positive relationship between the variables may become negative and vice versa.

2. Why does the sign of data change in regression analysis?

The sign of data may change in regression analysis due to the presence of outliers or influential data points, which can heavily influence the results of the analysis. It may also be due to the inclusion or exclusion of certain variables in the model.

3. How does changing sign of data affect the interpretation of regression results?

Changing sign of data can greatly impact the interpretation of regression results. It can lead to a different conclusion about the relationship between the variables and can affect the significance of the results. It is important to carefully consider the reasons for the change in sign before drawing any conclusions.

4. Can changing sign of data be corrected in regression analysis?

In some cases, changing sign of data can be corrected by addressing the underlying issues such as influential data points or variable selection. However, if the change in sign is due to a true change in the relationship between the variables, it cannot be corrected.

5. How can we prevent or minimize the impact of changing sign of data in regression analysis?

To prevent or minimize the impact of changing sign of data, it is important to carefully select and test the variables included in the regression model. It is also helpful to examine the data for outliers and influential points and consider removing them from the analysis. Additionally, performing sensitivity analysis can help determine the robustness of the results to potential changes in the data.

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