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Math Help - Regression Model Building

  1. #1
    Newbie
    Joined
    Oct 2009
    Posts
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    Regression Model Building

    Hi,

    I have a statistics homework assignment which I'm not sure how to best
    begin. My teacher gave me a set of data (car crashes at sites) that
    includes thousands of observations of count data (one dependent
    variable) with a large set of predictor variables (about 25). The
    dependent variable data has many zeros (many places didn't have
    crashes). I have to fit a parsimonious model that best explains the
    variation in the dependent variable with the smallest set of
    predictors.

    I'm not asking how to do the regression, but rather how to attack this
    problem. How do I decide what variables to keep? Do I start with all
    of the variables and consider those with the lowest t-statistic
    (highest P-value)? Or build up from variables which I think are
    important? How should I consider the R-square value? What else should
    I look for?

    I have begun with a negative binomial regression and trying out
    various models, but I'm not sure how to get to the best model. I'm
    using STATA to do the analysis.

    Any insight would be greatly appreciated! Thanks.
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  2. #2
    Grand Panjandrum
    Joined
    Nov 2005
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    someplace
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    Thanks
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    Quote Originally Posted by Artemis View Post
    Hi,

    I have a statistics homework assignment which I'm not sure how to best
    begin. My teacher gave me a set of data (car crashes at sites) that
    includes thousands of observations of count data (one dependent
    variable) with a large set of predictor variables (about 25). The
    dependent variable data has many zeros (many places didn't have
    crashes). I have to fit a parsimonious model that best explains the
    variation in the dependent variable with the smallest set of
    predictors.

    I'm not asking how to do the regression, but rather how to attack this
    problem. How do I decide what variables to keep? Do I start with all
    of the variables and consider those with the lowest t-statistic
    (highest P-value)? Or build up from variables which I think are
    important? How should I consider the R-square value? What else should
    I look for?

    I have begun with a negative binomial regression and trying out
    various models, but I'm not sure how to get to the best model. I'm
    using STATA to do the analysis.

    Any insight would be greatly appreciated! Thanks.
    Google principle component analysis (PCA) and or factor/analysis

    CB
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