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Quality and Reliability Methods - SAS

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Chapter 10 Variability Charts 173<br />

Attribute Gauge Charts<br />

As an example of the calculations, consider the following table of data for three raters, each having three<br />

replicates for one subject.<br />

Table 10.4 Three Replicates for Raters A, B, <strong>and</strong> C<br />

A B C<br />

1 1 1 1<br />

2 1 1 0<br />

3 0 0 0<br />

Using this table,<br />

4 5<br />

+<br />

2<br />

2<br />

<br />

% Agreement = ----------------------<br />

9<br />

2<br />

16<br />

= ----- = 0.444<br />

36<br />

4 + 3+<br />

3 10<br />

% Agreement [rater A] = % Agreement [rater B] = --------------------- = ----- = 0.476 <strong>and</strong><br />

8 + 7+<br />

6 21<br />

4+ 3+<br />

2<br />

% Agreement [rater C] = ---------------------<br />

8+ 7+<br />

6<br />

9<br />

= ----- = 0.4286<br />

21<br />

Agreement<br />

The Agreement Report gives agreement summarized for every rater as well as overall agreement.<br />

The Agreement Comparisons give Kappa statistics for each Y variable compared with all other Y variables.<br />

In other words, each rater is compared with all other raters.<br />

The Agreement within Raters report shows the number of items that were inspected. The confidence<br />

intervals are Score confidence intervals, as suggested by Agresti <strong>and</strong> Coull, (1998). The Number Matched is<br />

defined as the sum of number of items inspected, where the rater agreed with him or herself on each<br />

inspection of an individual item. The Rater Score is Number Matched divided by Number Inspected.<br />

The simple kappa coefficient is a measure of inter-rater agreement.<br />

where<br />

P 0<br />

– P e<br />

κˆ = ----------------<br />

1 – P e<br />

<strong>and</strong><br />

P 0<br />

=<br />

<br />

p ii<br />

i<br />

<br />

P e<br />

= p i.<br />

p .i<br />

i

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