# How do I create a composite with items with different scale ranges?

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How do I create a composite with items with different scale ranges?

• If you are going to composite together multiple items, all the items need to have the same scale range. Why? Lets say we ask two happiness questions: (1) "How happy are you right now?" on a 1-7 scale, and (2) "How happy do you feel?", on a -3 to 3 scale. Notice that the two questions are about the same construct (so theoretically you can merge them together), and also notice that the total range of the scales for both items are 7 points, BUT the scale ranges are along different dimensions. Compositing involves averaging items together. If we average together these two items, the resulting average will not be interpretable because of the different scale ranges. - A "1" on the first item is the lowest possible answer choice, but a "1" on the second item is one of the highest possible choices.
• The solution is to transform both scale ranges into a common metric. This is accomplished by first "standardizing" both items. Then, you composite the newly transformed items. It is worth pointing out that standardizing your items to transform items to a common metric is necessary when any of the scale ranges differ, not just with negative versus positive items, as in the example above. - Researchers sometimes ask questions about the same construct that are so similar that you want to vary the scale ranges of the items so that you tap into more information (and also force the subjects to pay more attention to the items because all items with the same scale range may allow lazy subjects to answer the same way on similar questions without thinking carefully about their answers).
• You can transform items with different scale ranges into the same metric by using standard statistically packages like SPSS and SAS which create the newly standardized variables and list it at the end of the data file. Each standardized variable is listed in a separate column. You can then analyze the new standardized variables as you would any other variable in your data set, including averaging them together to create a composite.

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