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elsabbagh_ahmed
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I have already carried out my experimental plan (not according to JMP). Can i implement the results in JMP and evaluate them with a different level of significance

I have already carried out my experimental plan (not according to JMP). Can i implement the results in JMP and evaluate them with a different level of significance

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Re: I have already carried out my experimental plan (not according to JMP). Can i implement the results in JMP and evaluate them with a different level of significance

Generally speaking JMP reports statistical inference statistics such as Prob > F ratios, Prob >|t|, etc. with p values which you can use to compare to any significance level threshold you want use. So there really isn't a significance level default value for various inferential decisions inherent in JMP's modeling platforms.

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Re: I have already carried out my experimental plan (not according to JMP). Can i implement the results in JMP and evaluate them with a different level of significance

Peter is correct in his statement, but I am looking at your question in a different way.  You can use stepwise regression and set the level of significance you are willing to accept for being right/wrong that a predictor is important or not to your model.  That would be set under stopping rule for P-value Threshold.  A rule of thumb is to set that value at 0.05 for leaving.  This translates into all of your important factors needing a P >|t| of 0.05 or less if they are to be included in the final model.  You can change that significance value to any value you choose, but I would recommend keeping it as low as possible.