Regression with summated scales: Example

Tables 14 and 15 present the results of a multiple regression analysis made with British data where the ‘General bad mood scale’ is the dependent variable, while the ‘Job-family time squeeze scale’ is one of the independent variables. We have also taken the liberty of including four single-indicator, ordinal variables. This is common practice but, as pointed out above, you should use summated scales if you have the right kind of indicator variables available. As demonstrated in chapter 6, you can also avoid the whole ordinal variable problem by recoding them into sets of dummy variables. In the case discussed here, however, where we use four ordinal independent variables, you may perhaps regard the total number of variables needed for this solution as too high for comfort. In any case, the four ordinal variables, used with their original coding scheme intact, are:

We have also included the respondent’s gender recoded as a dummy variable. The original gender variable applies other value codes (women = 2 and men = 1). There is nothing to prevent you from using this original variable instead of the dummy coded version, but it would change the value and interpretation of the constant term. (The estimate or interpretation of the gender variable’s coefficient would not be affected.)

Caution should be shown with respect to drawing causal inferences, but the results shown in table 14 at least seem to confirm that several factors affect people’s mood, including time squeeze problems, health problems and perceived financial problems.

Note also that it is essential that you know how the variables are coded, i.e. that you know what numerical values have been assigned to the different answers given to the survey questions. For instance, you need to know that the values of the variable ‘Feeling about household's present income’ ranges from 1 to 4, and that 1 stands for ‘Living comfortably on present income’, while 4 stands for ‘Very difficult on present income’. Knowing this enables you to see that the positive sign of this variable’s coefficient indicates that the average mood is worse among those who experience financial problems than among others. Make your own interpretations of the other coefficients’ signs. (Find out about how you can inspect a variable’s value codes here.

Table 14. SPSS output: Regression with summated scales coefficients

Table 15. Regression with summated scales regression goodness of fit statistics

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