Assign Preference Scores to Attributes:

Assign preference scores to the attributes such that a greater preference score represents a more valued attribute and a lower preference score represents a less valued attribute.

Select Types:

Benefit attributes are attributes such that a greater value is more preferable. Cost attributes are attributes such that a smaller value is more preferable.

Enter Attribute Values:

Enter the values for all treatment/attribute combinations.

Results will also be calculated by factoring in uncertainty. These values will be calculated by randomly selecting a value from a normal distirbution with mean equal to the corresponding certain value entered in the above table and standard deviation equal to the mean times the uncertainty factor entered below. The uncertainty factor entered below must be between 0 and 1.

Uncertainty Factor

Results:

Welcome to the treatment optimization app.
This app is designed to determine the optimal treatment method based on personal attribute weightings and potential attribute values.
This app will compare the results of the different weight-estimation methods.
1. Begin by selecting a decision-making method (SAW or TOPSIS) from the drop-down menu.
2. Select a starting table from the next drop-down menu. If you would like to create a custom table, select custom. Otherwise, select the pre-filled in table which you would like to simulate.
3. If you selected a pre-filled in table, skip to Step 6.
4. If you selected a custom table, enter the number of different treatments you would like to simulate.
5. If you selected a custom table, enter the number of attributes you would like to simulate.
6. Assign preference scores to each attribute based on how important each attribute is to you. A larger weight number indicates a more important attribute. Likewise, a smaller weight number indicates a less important attribute. Move the sliders to choose the weights. To increment/decrement a slider by 1, click on the slider and then press the left or right arrow key.
7. Select a type (Cost or Benefit) for each attribute. Benefit attributes are attributes such that a greater value is more preferable. Cost attributes are attributes such that a smaller value is more preferable.
8. Enter in all attribute values into the table.
9. Enter in the desired uncertainty factor. The uncertainty factor is used to calculate the values in the simulated uncertainty matrix. These values are calculated by randomly choosing a value from a normal distribution with mean equal to the corresponding value in the matrix with no uncertainty and with standard deviation equal to the mean times the uncertainty factor.
10. Check to make sure all of your entries are correct. If all of your entries are correct, proceed to Step 9.
11. Click the "Calculate" Button to view the results.

Main

Instructions

Treatment Optimization App

Assign Preference Scores to Attributes:

Select Types:

Enter Attribute Values:

Instructions