Answer to Question 1
Order effects occur when experience in one part of a research study affects performance in another part of the study. A simple example is fatigue: participants tire during one treatment condition and their performance is lower in the next treatment condition. As a result, there are two explanations for why the scores may differ from one treatment to another: the difference may be caused by the treatments, or the difference may be caused by order effects.
Answer to Question 2
Define the Focus: As in all of the scaling methods, you begin by defining the focus for your scale. Let's imagine that you want to develop a cumulative scale that measures U.S. citizen attitudes toward immigration. You would want to be sure to specify in your definition whether you are talking about any type of immigration (legal and illegal) from anywhere (Europe, Asia, Latin and South America, Africa).
Develop the Items: Next, as in all scaling methods, you would develop a large set of items that reflects the concept. You might do this yourself or you might en- gage a knowledgeable group to help. Of course, you would want to come up with many more statements (about 80100 is desirable) than you will ultimately need.
Rate the Items: Next, you would want to have a group of judges rate the statements or items in terms of how favorable they are to the concept of interest. They would give a Yes if the item is favorable toward the construct and a No if it is not. Notice that you are not asking the judges whether they personally agree with the statement. Instead, you're asking them to make a judgment about how the statement is related to the construct of interest.
Develop the Cumulative Scale: The key to Guttman scaling is in the analysis. You construct a matrix or table that shows the responses of all the respondents on all of the items. You then sort this matrix so that respondents who agree with more statements are listed at the top and those who agree with fewer are at the bottom. For respondents with the same number of agreements, sort the statements from left to right, from those that most agreed to, to those that fewest agreed to.
Although you can examine the matrix if there are only a few items in it, if there are many items, you need to use a data analysis procedure called scalogram analysis to determine the subsets of items from the pool that best approximate the cumulative property. Then, you review these items and select your final scale elements. There are several statistical techniques for examining the table to find a cumulative scale. Because there is seldom a perfectly cumulative scale, you usually have to test how good it is. These statistics also estimate a scale score value for each item. This scale score is used in the final calculation of a respondent's score.
Administering the Scale: After you've selected the final scale items, it's relatively simple to administer the scale. You simply present the items and ask respondents to check items with which they agree.
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