Plotslice tool from the statistics toolbox creates a figure containing a series of plots, each representing a slice through the regression surface predicted by the model. In case of multiple predictor variables, there is an effect of the choice of predictor variables that change the confidence bounds.
From the function coefsCI i can generate the confidence intervel of the coefficients of the model. In my case i am using a logistic model with 5 parameters and 2 interactions. I find that the surface i generate with the aid of the coefsCI are too wide compared to the bounds generated by plot slice. So wide that the the lower bound of probability stays zero where as the upper bound is 1.
Is there any difference in the method that is used to calculate the bounds in case of plotslice?
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