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Design-Expert v22.0
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Installation
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Analysis
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Python Integration (Stat-Ease 360
®
only)
Advanced Topics
Logistic Regression
Candidate Point Creation
Complex Constraints
Convert Coded response surface model to Actual
Converting Mixture Models from Pseudo to Real
Convert a quadratic L_Pseudo mixture model to Real
Convert a quadratic U_Pseudo mixture model to Real
Covariates and Additional Explanatory Variables
Design Augmentation
Equation Entry
Exponential Notation
Extrapolating a Mixture Design
Extrapolating a Response Surface Design
Foldover
Fraction of Design Space Computations
Fraction of Paired Design Space computations
Interpreting Models
Mean Bias Correction
Multiple Linear Constraints
Optimality Criteria
Optimal Exchange Methods
Propagation of Error
Standardized and Normalized Factorial Effects
Start the Design From Existing Data
Restricted Maximum Likelihood (REML) vs Maximum Likelihood (ML) Analysis
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Design-Expert
»
Advanced Topics
»
Logistic Regression
» Fit Statistics
Fit Statistics
Pseudo R-Squared
McFadden
Adjusted McFadden
Tjur
Predicted Mean
Parameters
Goodness-of-fit Tests
Pearson Chi-Squared Test
Deviance Chi-Squared Test
Hosmer-Lemeshow Chi-Squared Test
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