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Is it appropriate to do a multiple logistic regression where both the dependent and independent variables are binary?

Or, can I only use simple logistic regression?

What's the difference between these two methods?

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    $\begingroup$ Multiple logistic regression means you have more than one predictor. Simple logistic regression is when you only have one predictor. In both cases you can use both categorical and continuous predictors. $\endgroup$
    – Macro
    Jun 23 '12 at 16:23
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The difference between a multiple logistic regression and a simple logistic regression is that the multiple regression -- by definition -- includes more than one regressor! Both models can handle categorical and continuous variables, or any combination thereof.

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    $\begingroup$ To downvoters and flaggers: it is perfectly legitimate for anybody to jump in with an answer that echoes (or even copies) a comment which happens to contain a solution to the problem that is posed. This is because answers have more status on our site (in terms of searches, community votes, and opportunities for improvement): it is preferable that solutions appear as answers rather than buried in the comments. So please vote on this answer based on its merits, rather than on its apparent originality or lack thereof. $\endgroup$
    – whuber
    Jun 23 '12 at 21:12

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