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R Statistical Application Development by Example Beginner's Guide by Prabhanjan Narayanachar Tattar

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Time for action – diagnostics for the logistic regression

The influence and leverage points will be identified through the application of the functions, such as hatvalues, cooks.distance, dffits, and dfbetas for the pass_logistic fitted model.

  1. The high leverage points of a logistic regression model are obtained with hatvalues(pass_logistic) while the Cooks distance is fetched with cooks.distance(pass_logistic). The DFFITS and DFBETAS measures of influence are obtained by running dfbetas(pass_logistic) and dffits(pass_logistic).
  2. The influence and leverage measures are put together using the cbind function:
    cbind(hatvalues(pass_logistic),cooks.distance(pass_logistic),dfbetas(pass_logistic),dffits(pass_logistic))

    The output is given in the following ...

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