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Posted 06-18-2018 12:44 PM
(1544 views)

I am running a logistic regression that includes several covariates, and has a binary outcome. I have 2 variables that I am interested in that I want to determine and comment on their predictive validity. I have run models with just these two predictors, and have also run models included all the covariates. I compared ROC curves for each, and commented on p-values.

Are there other good tests that SAS can perform to check predictive validity?

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"predictive validity" isn't really a term used in statistics; however you may mean something like "is the term statistically significant" in the model. This is the Pr>ChiSq output. A common cutoff is 0.05, if Pr>ChiSq is less than 0.05, then the term is statistically significant.

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Paige Miller

Paige Miller

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@SAS_BK wrote:

You seem to be running into difficulties that happen when your input variables are correlated with one another. Then, there is no unique way to determine the true effect of that variable, and in fact, depending on the terms in the model, the effect of the variable might be large or might be small, and depending on the amount of correlation, a variable could have the wrong sign.

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Paige Miller

Paige Miller

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What would you recommend to check collinearity issues between my variables?

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The simple correlation between two variables is what you need to check.

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Paige Miller

Paige Miller

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PROC PLS is a good friend with you.

You can check the importance of variables in model by it.

The more important a variable is ,and it has more predictive power.

Check PROC PLS 's documentation, there is already an example about it .

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