Basic Analysis • Logistic Analysis
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Logistic Analysis
Examine Relationships between a Categorical Y and a Continuous X Variable
The Logistic platform fits the probabilities for response categories to a continuous x predictor. The fitted model estimates probabilities for each x value. The Logistic platform is the nominal or ordinal by continuous personality of the Fit Y by X platform. There is a distinction between nominal and ordinal responses on this platform:
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Nominal logistic regression estimates a set of curves to partition the probability among the responses.
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Ordinal logistic regression models the probability of being less than or equal to a given response. This has the effect of estimating a single logistic curve, which is shifted horizontally to produce probabilities for the ordered categories. This model is less complex and is recommended for ordered responses.
Figure 7.69 Examples of Logistic Regression
Contents 
Overview of Logistic Regression
Nominal Logistic Regression
Ordinal Logistic Regression
Example of Nominal Logistic Regression
Launch the Logistic Platform
Data Structure
The Logistic Report
Logistic Plot
Iterations
Whole Model Test
Fit Details
Parameter Estimates
Logistic Platform Options
ROC Curves
Save Probability Formula
Inverse Prediction
Additional Examples of Logistic Regression
Example of Ordinal Logistic Regression
Additional Example of a Logistic Plot
Example of ROC Curves
Example of Inverse Prediction Using the Crosshair Tool
Example of Inverse Prediction Using the Inverse Prediction Option
Statistical Details for the Logistic Platform

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Help created on 10/11/2018