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Thread: Assumptions of logistic regression

  1. #46
    Fortran must die
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    Re: Assumptions of logistic regression




    lol I bet that was fun.

    Probably won't be bringing this up at the next faculty luncheon. "We have been teaching our course wrong for n years and we have a link associated with the university demonstrating that mistake"
    "Very few theories have been abandoned because they were found to be invalid on the basis of empirical evidence...." Spanos, 1995

  2. #47
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    Re: Assumptions of logistic regression

    It was alright actually.

    Quote Originally Posted by Markus
    Dason,
    You are right that normality is not necessarily required in the predictor; all you need is for the error to be normally distributed. However, often distributional problems in the predictor allow you to avoid problems later on. For instance, if you use something like income (a heavily skewed variable) to predict, say, life satisfaction, you will always find that you are creating a much more meaningful and also statistically sound model when you log-transform the predictor.
    Which I agree with. But that's more because the response is more of a log relationship between income and satisfaction - it doesn't have to do with the distribution of the predictor.

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  4. #48
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    Re: Assumptions of logistic regression


    His (or her) comment is pretty much identical to say Fidel and I suspect everyone else who makes this type of comment. What they fail to understand is that they confuse the heck out of people like me who don't catch the distinction they are making here ( I think Fidel does make it clear that this is only a tool to address problems not an assumption of the method, her discussion of it is in a general data clean up section not a method by itself).
    "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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