The reason for wanting to check the method of computing the composite may be because:

- You want to verify that the composite was created correctly
- You are returning to the dataset after a long hiatus and have forgotten exactly how it was computed
- The composite was computed by someone else

- these items are used to calculate two or more subtotals each based on a subset of items
- the scores and subtotals may be based on a set of items after some items have been removed
- some items may have been reversed
- you may have made a decision about whether to use a total or a mean score.

**GENERAL PROCEDURE**

Let’s look at some examples.

**Example 1.**

Take a 12 item scale.In SPSS I computed a total score based on all items.

COMPUTE qtot=mean(q1 to q12)*12.

In SPSS Press: Analyze : Regression : Linear

Independents = all 12 items

Dependent = Total Score

Note how the r-squared is 1.00 and the unstandardised regression coefficients are all 1.00.

This reflects the fact that:

TOTAL = 1*q1 + 1*q2 + … + 1*q12

**Example 2.**

Once again imagine a scale with 12 items. This time imagine that you have forgotten how the total was calculated. You are pretty sure that some items were reversed and some excluded, but which ones were they.

Analyze : Regression : Linear

Independents = all 12 items

Dependent = Total Score

The above table shows that the total is a function of the items (R-squared = 1.00).

Items 2 and 3 were reversed (see the -1.00 unstandardized coefficients)

Items 1, 9, 11, and 12 were excluded (see the unstandardised coefficients are all essentially zero).

Thus, if you need to check how a composite was coded, a multiple regression is a useful tool.

It is also good advice to store as syntax any commands that compute composite scores.

If you don’t get an r-squared of 1, there are many possible explanations: items have been left out of the composite; something was problematic with your method of computing the composite; etc.

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