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Bias – none
Measured on the High Level Specimen 24 Precision – good
22
20
18
16

Measured on the High Level Specimen 24 Biased Precision – poor
22
20
18
Biased
16
6 8 10 12 14 6 Bias – poor 12 14
8
10
Measured on the Measured on the
Low Level Specimen Low Level Specimen
FIGURE 9.2 Four possible Youden plots. Bias is judged with respect to the 45° diagonal. The lower-left panel shows two
labs that are biased high specimens and one lab that is biased low. The lower-right panel shows all labs with high bias,
presumably because of some weakness in the measurement protocol.

because of some weakness in the measurement protocol. Additional interpretation of the Youden plot is
possible. Consult Youden and Steiner (1975), Woodside and Kocurek (1997), or Miller and Miller (1984)
for details.

Ruggedness Testing
Before a test method is recommended as a standard for general use, it should be submitted to a ruggedness
test. This test evaluates the measurement method when small changes are made in selected factors of the
method protocol. For example, a method might involve the pH of an absorbing solution, contact time,
temperature, age of solution, holding time-stored test specimens, concentration of suspected interfer-
ences, and so on. The number of factors (k) that might influence the variability and stability of a method
can be quite large, so an efficient strategy is needed.
One widely used design for ruggedness tests allows a subset of k = 7 factors to be studied in Ν = 8
7−4
trials, with each factor being set at two levels (or versions). Table 9.2 shows that this so-called 2
fractional factorial experimental design can assess seven factors in eight runs (ASTM, 1990). The pluses

TABLE 9.2
7– 4
A 2 Fractional Factorial Design for Ruggedness Testing
Factor Observed
Run 1 2 3 4 5 6 7 Response
1 − − − + + + − y 1
2 + − − − − + + y 2
3 − + − − + − + y 3
4 + + − + − − − y 4
5 − − + + − − + y 5
6 + − + − + − − y 6
7 − + + − − + − y 7
8 + + + + + + + y 8

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