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Practical Data Analysis with JMP® by Robert Carver

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Non-Linear Relationships

Whole Model Test

This portion of the output compares the performance of our specified model with a naive default model with no predictor variables. The naive model essentially posits that, based on the sample ratio of 8/32 or 25% of the patients having no disease, there is a probability of 0.75 that a tested patient has PD. In this panel, the Chi-Square test is analogous to the customary F test and in this analysis, we find a significant result. In other words, this model is an improvement over simply estimating a 0.75 probability of PD.

We also find RSquare (U), which is analogous to R2 as a goodness-of-fit statistic. This model provides an unimpressive value of 0.34, indicating a lot of unexplained variation. Such ...

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