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JMP_DOE官方使用教程.pdf
Introduction to Designing Experiments
About Designing Experiments
My First Experiment
The Situation
Step 1: Design the Experiment
Define the Responses: Popped Kernels and Total Kernels
Define the Factors: Time, Power, and Brand
Step 2: Define Factor Constraints
Step 3: Add Interaction Terms
Step 4: Determine the Number of Runs
Step 5: Check the Design
Step 6: Gather and Enter the Data
Step 7: Analyze the Results
Examples Using the Custom Designer
Creating Screening Experiments
Creating a Main-Effects-Only Screening Design
Creating a Screening Design to Fit All Two-Factor Interactions
A Compromise Design Between Main Effects Only and All Interactions
Creating ‘Super’ Screening Designs
The Need for Supersaturated Designs
Example: Twelve Factors in Eight Runs
Screening Designs with Flexible Block Sizes
Checking for Curvature Using One Extra Run
Creating Response Surface Experiments
Exploring the Prediction Variance Surface
Introducing I-Optimal Designs for Response Surface Modeling
A Three-Factor Response Surface Design
Response Surface with a Blocking Factor
Creating Mixture Experiments
Mixtures Having Nonmixture Factors
Experiments that are Mixtures of Mixtures
Special-Purpose Uses of the Custom Designer
Designing Experiments with Fixed Covariate Factors
Creating a Design with Two Hard-to-Change Factors: Split Plot
Technical Discussion
Building Custom Designs
Creating a Custom Design
Enter Responses and Factors into the Custom Designer
How to Enter Responses
Specifying Response Goal Types and Lower and Upper Limits
Understanding Response Importance Weights
Adding Simulated Responses, If Desired
How to Enter Factors
Factors that are Easy, Hard, or Very Hard, to Change: Creating Optimal Split-Plot and Split-Split-Plot Designs
Defining Factor Constraints, If Necessary
Describe the Model
Specifying Alias Terms
Select the Number of Runs
Understanding Design Evaluation
The Prediction Variance Profile
The Fraction of Design Space Plot
The Prediction Variance Surface
The Relative Variance of Coefficients and Power Table
The Alias Matrix (Confounding Pattern)
Color Map on Correlations
The Design Diagnostics Table
Specify Output Options
Make the JMP Design Table
Creating Random Block Designs
Creating Split Plot Designs
Creating Split-Split Plot Designs
Creating Strip Plot Designs
Special Custom Design Commands
Save Responses and Save Factors
Load Responses and Load Factors
Save Constraints and Load Constraints
Set Random Seed: Setting the Number Generator
Simulate Responses
Save X Matrix: Viewing the Number of Rows in the Moments Matrix and the Design Matrix (X) in the Log
Optimality Criterion
Number of Starts: Changing the Number of Random Starts
Why Change the Number of Starts?
Default Choice of Number of Random Starts: Technical Information
Sphere Radius: Constraining a Design to a Hypersphere
Disallowed Combinations: Accounting for Factor Level Restrictions
Advanced Options for the Custom Designer
Changing the Search Points Per Factor
Altering the Mixture Sum
Split Plot Variance Ratio
Prior Parameter Variance
D Efficiency Weight
Save Script to Script Window
Assigning Column Properties
Define Low and High Values (DOE Coding) for Columns
Set Columns as Factors for Mixture Experiments
Define Response Column Values
Assign Columns a Design Role
Identify Factor Changes Column Property
How Custom Designs Work: Behind the Scenes
Screening Designs
Screening Design Examples
Using Two Continuous Factors and One Categorical Factor
Using Five Continuous Factors
Creating a Screening Design
Enter Responses
Specifying Goal Types and Lower and Upper Limits
Understanding Importance Weights
Enter Factors
Types of Factors
Choose a Design
Two-Level Full Factorial
Two-Level Fractional Factorial
Plackett-Burman Designs
Mixed-Level Designs
Cotter Designs
Display and Modify a Design
Aliasing of Effects
Look at the Confounding Pattern
Understanding Design Codes
Changing the Coded Design
Specify Output Options
View the Design Table
Create a Plackett-Burman design
Analysis of Screening Data
Using the Screening Analysis Platform
Using the Fit Model Platform
The Actual-by-Predicted Plot
The Scaled Estimates Report
A Power Analysis
Response Surface Designs
A Box-Behnken Design: The Tennis Ball Example
The Prediction Profiler
A Response Surface Plot (Contour Profiler)
Geometry of a Box-Behnken Design
Creating a Response Surface Design
Enter Responses and Factors
Choose a Design
Box-Behnken Designs
Central Composite Designs
Specify Axial Value (Central Composite Designs Only)
Specify Output Options
View the Design Table
Full Factorial Designs
The Five-Factor Reactor Example
Analyze the Reactor Data
Creating a Factorial Design
Enter Responses and Factors
Select Output Options
Make the Table
Mixture Designs
Mixture Design Types
The Optimal Mixture Design
Adding Effects to the Model
The Simplex Centroid Design
Creating the Design
Simplex Centroid Design Examples
The Simplex Lattice Design
The Extreme Vertices Design
Creating the Design
An Extreme Vertices Example with Range Constraints
An Extreme Vertices Example with Linear Constraints
Extreme Vertices Method: How It Works
The ABCD Design
Creating Ternary Plots
Fitting Mixture Designs
Whole Model Tests and Analysis of Variance Reports
Understanding Response Surface Reports
A Chemical Mixture Example
Create the Design
Analyze the Mixture Model
The Prediction Profiler
The Mixture Profiler
A Ternary Plot of the Mixture Response Surface
Discrete Choice Designs
Introduction
Create an Example Choice Experiment
Analyze the Example Choice Experiment
Design a Choice Experiment Using Prior Information
Administer the Survey and Analyze Results
Initial Choice Platform Analysis
Find Unit Cost and Trade Off Costs with the Profiler
Space-Filling Designs
Introduction to Space-Filling Designs
Sphere-Packing Designs
Creating a Sphere-Packing Design
Visualizing the Sphere-Packing Design
Latin Hypercube Designs
Creating a Latin Hypercube Design
Visualizing the Latin Hypercube Design
Uniform Designs
Comparing Sphere-Packing, Latin Hypercube, and Uniform Methods
Minimum Potential Designs
Maximum Entropy Designs
Gaussian Process IMSE Optimal Designs
Borehole Model: A Sphere-Packing Example
Create the Sphere-Packing Design for the Borehole Data
Guidelines for the Analysis of Deterministic Data
Results of the Borehole Experiment
Accelerated Life Test Designs
Overview of Accelerated Life Test Designs
Using the ALT Design Platform
Platform Options
Example
Nonlinear Designs
Examples of Nonlinear Designs
Using Nonlinear Fit to Find Prior Parameter Estimates
Creating a Nonlinear Design with No Prior Data
Creating a Nonlinear Design
Identify the Response and Factor Column with Formula
Set Up Factors and Parameters in the Nonlinear Design Dialog
Enter the Number of Runs and Preview the Design
Make Table or Augment the Table
Advanced Options for the Nonlinear Designer
Taguchi Designs
The Taguchi Design Approach
Taguchi Design Example
Analyze the Data
Creating a Taguchi Design
Detail the Response and Add Factors
Choose Inner and Outer Array Designs
Display Coded Design
Make the Design Table
Augmented Designs
A D-Optimal Augmentation of the Reactor Example
Analyze the Augmented Design
Creating an Augmented Design
Replicate a Design
Add Center Points
Creating a Foldover Design
Adding Axial Points
Adding New Runs and Terms
Special Augment Design Commands
Save the Design (X) Matrix
Modify the Design Criterion (D- or I- Optimality)
Select the Number of Random Starts
Specify the Sphere Radius Value
Disallow Factor Combinations
Prospective Sample Size and Power
Launching the Sample Size and Power Platform
One-Sample and Two-Sample Means
Single-Sample Mean
Power versus Sample Size Plot
Power versus Difference Plot
Sample Size and Power Animation for One Mean
Two-Sample Means
Plot of Power by Sample Size
k-Sample Means
One Sample Standard Deviation
One Sample Standard Deviation Example
One-Sample and Two-Sample Proportions
One Sample Proportion
One-Sample Proportion Window Specifications
Two Sample Proportions
Two Sample Proportion Window Specifications
Counts per Unit
Counts per Unit Example
Sigma Quality Level
Sigma Quality Level Example
Number of Defects Computation Example
Reliability Test Plan and Demonstration
Reliability Test Plan
Example
Reliability Demonstration
Example
Index
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W-Z
Version 9
Design of Experiments
Guide
“The real voyage of discovery consists not in seeking new
landscapes, but in having new eyes.”
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9.0.2
The correct bibliographic citation for this manual is as follows: SAS Institute Inc. 2010. JMP® 9 Design
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Contents
Design of Experiments
1
Introduction to Designing Experiments
A Beginner’s Tutorial
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
About Designing Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
My First Experiment
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
The Situation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Step 1: Design the Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Step 2: Define Factor Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Step 3: Add Interaction Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Step 4: Determine the Number of Runs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Step 5: Check the Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Step 6: Gather and Enter the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Step 7: Analyze the Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2 Examples Using the Custom Designer
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15
Creating Screening Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Creating a Main-Effects-Only Screening Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Creating a Screening Design to Fit All Two-Factor Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
A Compromise Design Between Main Effects Only and All Interactions . . . . . . . . . . . . . . . . . . . . 21
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Creating ‘Super’ Screening Designs
Screening Designs with Flexible Block Sizes
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Checking for Curvature Using One Extra Run . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Creating Response Surface Experiments
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Exploring the Prediction Variance Surface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Introducing I-Optimal Designs for Response Surface Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
A Three-Factor Response Surface Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
Response Surface with a Blocking Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
Creating Mixture Experiments
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
Mixtures Having Nonmixture Factors
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
Experiments that are Mixtures of Mixtures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
ii
Special-Purpose Uses of the Custom Designer
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Designing Experiments with Fixed Covariate Factors
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Creating a Design with Two Hard-to-Change Factors: Split Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Technical Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3 Building Custom Designs
The Basic Steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Creating a Custom Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Enter Responses and Factors into the Custom Designer
Describe the Model
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
Specifying Alias Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
Select the Number of Runs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Understanding Design Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
Specify Output Options
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
Make the JMP Design Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Creating Random Block Designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Creating Split Plot Designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Creating Split-Split Plot Designs
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
Creating Strip Plot Designs
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
Special Custom Design Commands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Save Responses and Save Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
Load Responses and Load Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
Save Constraints and Load Constraints
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
Set Random Seed: Setting the Number Generator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
Simulate Responses
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
Save X Matrix: Viewing the Number of Rows in the Moments Matrix and the Design Matrix (X) in the
Log . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
Optimality Criterion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
Number of Starts: Changing the Number of Random Starts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
Sphere Radius: Constraining a Design to a Hypersphere . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Disallowed Combinations: Accounting for Factor Level Restrictions
. . . . . . . . . . . . . . . . . . . . . . . 90
Advanced Options for the Custom Designer
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Save Script to Script Window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Assigning Column Properties
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
Define Low and High Values (DOE Coding) for Columns
Set Columns as Factors for Mixture Experiments
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Define Response Column Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
iii
Assign Columns a Design Role . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Identify Factor Changes Column Property . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
How Custom Designs Work: Behind the Scenes
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4 Screening Designs
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Screening Design Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Using Two Continuous Factors and One Categorical Factor
. . . . . . . . . . . . . . . . . . . . . . . . . . . .
Using Five Continuous Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
103
103
105
Creating a Screening Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Enter Responses
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Enter Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
Choose a Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
111
Display and Modify a Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Specify Output Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
View the Design Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
Create a Plackett-Burman design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
Analysis of Screening Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
122
Using the Screening Analysis Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Using the Fit Model Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
124
5 Response Surface Designs
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
127
A Box-Behnken Design: The Tennis Ball Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
129
The Prediction Profiler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
134
A Response Surface Plot (Contour Profiler) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Geometry of a Box-Behnken Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
136
136
Creating a Response Surface Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Enter Responses and Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
137
Choose a Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
Specify Output Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
139
View the Design Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
6 Full Factorial Designs
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
143
The Five-Factor Reactor Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
Analyze the Reactor Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
Creating a Factorial Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
iv
Enter Responses and Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
152
Select Output Options
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Make the Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
152
7 Mixture Designs
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
Mixture Design Types
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
157
The Optimal Mixture Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
157
158
The Simplex Centroid Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Creating the Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
159
Simplex Centroid Design Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
The Simplex Lattice Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
161
The Extreme Vertices Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
163
Creating the Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
An Extreme Vertices Example with Range Constraints
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
An Extreme Vertices Example with Linear Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
Extreme Vertices Method: How It Works
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
The ABCD Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
Creating Ternary Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
Fitting Mixture Designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
171
171
Whole Model Tests and Analysis of Variance Reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Understanding Response Surface Reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
171
A Chemical Mixture Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
171
Create the Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
Analyze the Mixture Model
175
The Prediction Profiler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The Mixture Profiler
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
A Ternary Plot of the Mixture Response Surface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
8 Discrete Choice Designs
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
Create an Example Choice Experiment
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
183
Analyze the Example Choice Experiment
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
Design a Choice Experiment Using Prior Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
188
Administer the Survey and Analyze Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
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