Enter your data for Response Optimizer

Complete the following steps to specify the responses to include in response optimization.

This dialog box varies by the type of model that you used to fit the data.

In This Topic

Models from the Predictive Analytics Module
Models from the Stat menu except mixture designs
Mixture designs

Models from the Predictive Analytics Module

Go to the results for a Linear Regression model or for a Binary Logistic Regression model, then select Response Optimizer.
In the table, in Goal, select one of the following options for the response.
- Do not optimize: Do not include the response in the optimization process.
- Minimize: Lower values of the response are preferable.
- Target: The response is optimal when values meet a specific target value.
- Maximize: Higher values of the response are preferable.
For more information, go to Which response optimization goal should I use?.
In Target, for each response that has a goal of target, enter a target value. With a binary response, the target value must be between 0 and 1.

Models from the Stat menu except mixture designs

Note

Only response variables with up-to-date models from the same type of analysis are in the list. If you do not see a response that you want, re-fit the model. For more information, go to Stored model overview.

To perform this analysis in Minitab, go to the menu that you used to fit the model, then choose Response Optimizer. For example, if you fit a Poisson model, choose Stat > Regression > Poisson Regression > Response Optimizer.
In the table, in Goal, select one of the following options for each response.
- Do not optimize: Do not include the response in the optimization process.
- Minimize: Lower values of the response are preferable.
- Target: The response is optimal when values meet a specific target value.
- Maximize: Higher values of the response are preferable.
For more information, go to Which response optimization goal should I use?.
In Target, for each response that has a goal of target, enter a target value. With a binary response, the target value must be between 0 and 1.

Mixture designs

To perform response optimization for a mixture design, choose Stat > DOE > Mixture > Response Optimizer.
Move the variables that you want to include in the response optimization from the Available list to the Selected list.
Under Model Fitted in, choose whether you want to refit the model in Proportions or Pseudocomponents. For more information, go to Amounts, proportions, and pseudo-components scales for representing the data in a mixtures design and What is a pseudo-component?.
You must click Setup and specify the goal, boundaries, weight, and importance for each response variable before you can perform the analysis.