Designs paired comparison

Figure 15.13 Factor combinations for a randomized paired comparison design investigating the effect of temperature. Fruit number is an arbitrarily assigned, qualitative factor. Numbers beside factor combinations indicate the time order in which experiments are run.

Up to this point, the randomized paired comparison design has not offered any great improvement over the completely randomized design. However, the fact that each fruit has been investigated at a pair of temperatures allows us to carry out a... 

Randomized paired comparison experimental design for determining the effect of temperature on a wine-making system. 

Thus, the randomized paired comparison design has allowed a more sensifive way of viewing our data, a view that ignores much of the variation caused by the use of different fruits and focuses on pairwise differences associated with the single factor of interest, temperature. 

The randomized paired comparison design discussed in the previous section separates the effect of a qualitative factor, fruit, from the effect of a quantitative factor, temperature (see Section 1.2). The randomized complete block design discussed in this section allows us to investigate more than one purely qualitative variable and to estimate their quantitative effects. 

Figure 15.16 Sums of squares and degrees of freedom tree for the randomized paired comparison design.

Suppose someone comes to you with the hypothesis that shoes worn on the right foot receive more wear than shoes worn on the left foot. Design a randomized paired comparison experiment to test this hypothesis. How might it differ from a completely randomized design ... 

In the previous section, the discussion following Equation 12.15 suggested that certain experimental designs could be used to decrease the uncertainty associated with a parameter estimate by minimizing the effect of uncontrolled factors. In this section we discuss one of these experimental designs, the randomized paired comparison design. 

Paired-comparison designs, in which each subject serves as his/her own control, are also common.The same subject might receive both treatments at the same time, such as on two distinct and separate lesions on the body. Care must usually be taken in the protocol to make sure the separately treated areas on the same patient are as equivalent as possible in the disease under study. 

The next task is to prioritize and select a design by filtering through a number of design concepts to the point where just one is pursued for further development. Two techniques are very helpful in this regard Paired Comparison Analysis and Pugh Matrix. You can also use both of these techniques... 

Use Paired Comparison Analysis when you need to compare either more upstream innovation ideas or more downstream design concepts. This technique is especially helpful when you don t have objective data regarding how different ideas could meet your customers outcome expectations (see Technique 2), or when you re uncertain about how different design concepts could meet customer performance and perception expectations (see Technique 30). 

Analytical methods can be sub-divided into difference tests and descriptive analysis. Difference tests such as triangle and paired comparison tests are designed to identify differences between samples. In a triangle test, the assessor is given three samples, two of which are the same, and asked to identify which sample is different. In a paired comparison test, the assessor is asked to identify whether there is a difference in a particular sensory characteristic between a pair of samples. Descriptive analysis, in which the sensory characteristics of a sample are described and scored on a scale, is probably the most important analytical method. 

---