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Thread: increasing the r squared

  1. #16
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    Re: increasing the r squared




    thanks im getting this now

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    Re: increasing the r squared

    One thing to remember, and it is easy to forget, is that you can get everything right and still have poor R squared values. If the pheneomenon is really complex no small set of variables may in fact explain much.
    "Very few theories have been abandoned because they were found to be invalid on the basis of empirical evidence...." Spanos, 1995

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    Re: increasing the r squared

    whats considered poor ideally i would like 1, but i know that aint happening also is the durban watson test worth looking at in terms of being over 0.8 for auto correlation
    Last edited by diesel20056; 12-19-2011 at 04:39 PM. Reason: grammar

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    Re: increasing the r squared

    Do you have time series data (normally the only reason you check Durbin-Watson).
    "Very few theories have been abandoned because they were found to be invalid on the basis of empirical evidence...." Spanos, 1995

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    Re: increasing the r squared

    whats considered poor ideally i would like 1
    I don't know of anyone who has ever achieved this with empirical datasets. As to what is considered poor, that depends on your system. In physiology, where patterns of covariation are typically governed by tight constraints (e.g. receptor binding affinities, cardiac output, etc.), "good" r-squared values are likely to be high. For ecological data (e.g. influence of rain on mating probability of frogs), "good" r-squared values might be very low (0.25). This is why people typically don't examine r-squared during the model simplification process. We just look for the best model for the data we have, assuming that the data we collected can adequately address the question on hand. Even adjusted r-squared (which accounts somewhat for model complexity) has been shown to perform worse than AIC for selecting the simplest and best explanatory models, especially for data with nonlinearities.

    You're smart to look for autocorrelation in your data. I would be more interested to know if you have repeated-measures data (more than one data row or measurement per individual).

    Good luck. Sounds like a cool data set!

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    Re: increasing the r squared

    jpkelly makes a really good point. What is a good value depends entirely on what you are measuring. Certain phenomenon are very complex (meaning many factors contribute to them) and thus will have much lower r squared values than other phenomenon. The best idea is to look at journals in the area, or trade publications, and see what types of r squared values they have for similar studies.
    "Very few theories have been abandoned because they were found to be invalid on the basis of empirical evidence...." Spanos, 1995

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    Re: increasing the r sqaured

    Quote Originally Posted by noetsi View Post
    I always thought that if you transformed the Y value to a log you had to do the same to all predictor variables.
    I don't think this is true. But then again, I guess it depends. In what kind of situation would you transform all the predictor variables?

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    Re: increasing the r squared

    I thought, although it appears that I was wrong after reading more, that since you logged the left hand of the equation (the dependent variable) you had to log the right hand of the equation as well (the predictor variables). Much as if you multiply one side of an equation by a constant you have to multiply the other side.

    But again I find my long assumed views are wrong in this regard....
    "Very few theories have been abandoned because they were found to be invalid on the basis of empirical evidence...." Spanos, 1995

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    Re: increasing the r squared

    thanks all for the help

  10. #25
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    Re: increasing the r squared

    You are welcome.

    Incidently what is really important is getting the model right not getting a high r squared value
    "Very few theories have been abandoned because they were found to be invalid on the basis of empirical evidence...." Spanos, 1995

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    Re: increasing the r squared


    Incidently what is really important is getting the model right not getting a high r squared value
    Yes, noetsi is right! Very important!

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