unable to test linearity assumption of logistic regression. Hello, I am doing a simple binary logistic regression with the following structure: logit(Y) = a + bX X is
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In statistics, multicollinearity (also collinearity) is a phenomenon in which two or more predictor variables in a multiple regression model are highly correlated
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Just to add to what Dirk said about the Condition Number method, a rule of thumb is that values of CN > 30 indicate severe collinearity. Other methods, apart from
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Does anyone have any knowledge and/or experience in how to measure collinearity between categorical variables that have more than 2 categories in the context of
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unable to test linearity assumption of logistic regression. Hello, I am doing a simple binary logistic regression with the following structure: logit(Y) = a + bX X is

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In statistics, multicollinearity (also collinearity) is a phenomenon in which two or more predictor variables in a multiple regression model are highly correlated

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Just to add to what Dirk said about the Condition Number method, a rule of thumb is that values of CN > 30 indicate severe collinearity. Other methods, apart from

Read More

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Does anyone have any knowledge and/or experience in how to measure collinearity between categorical variables that have more than 2 categories in the context of

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