You may want to acquaint yourself with the RSiteSearch() function, the maintainer() function, and reading source code of libraries as first steps toward understanding how to implement these algorithms yourself.

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Sent from my phone. Please excuse my brevity.

Turgut Durduran wrote:

Hello all,

Evidently my previous message met some filter due to subject line. I am

re-sending my message. I apologize if this was sent out twice.

Based on "Ripley & Thompson, Analyst, 1987", I am trying to do a

regression of my data which assumes a linear

relationship between measurements by two modalities of the same

physiological parameter. The complication is that my errors are

heterogeneous, i.e. not only both X & Y variables have significant

variances, their ratio and individual values differ greatly between

subjects. I believe a simple linear regression (which ignores the

variances) is underestimating the slope of the relationship while a

method like deming regression is overestimating (or underestimating

depending on what I give as the ratio) since it assumes a constant

ratio

of the variable. Therefore, I have concluded that I need to do the full

MLFR type of analysis suggested in that paper.

Looking through

archives and such, I could not find a direct implementation for R. I

think a related method is that implemeted in "leiv" package which

implements errors-in-variables methods.

Admittedly, I am bit lazy

and I did not dig into "leiv" implementation to figure out the

differences and whether giving the ratio of the standard errors of Y to

those of X for each point actually is correct.

I am wondering if anyone has implemented this method in R and has an

example that I can look that.

While at it,? I am wondering what is the way to estimate the 95%

confidence interval in the results both for "leiv" and "MLFR".

Thanks,

Turgut?

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