The two theories combined

The following step is undertaken to assess which of the two theories, as operationalised here, is the most powerful determinant of social trust. We can do this by means of ordinary least square (OLS) regression. By including the two constructed variables as independent variables, and the trust variable as the dependent variable, we can measure the effect.

  1. Perform the regression analysis. Please remember to use the factor score variable and the logarithm of membership and involvement index variable. You must also remember to use the combined weight. Interpret the regression equation (y=a+b1x1+b2x2). SPSS
    REGRESSION
    /MISSING LISTWISE
    /STATISTICS COEFF OUTS R ANOVA
    /CRITERIA=PIN(.05) POUT(.10)
    /NOORIGIN
    /DEPENDENT ppltrst
    /METHOD=ENTER ln_org fac_suc.
  1. Which of the theories seems to explain most of the variation on the trust variable? Solution

    Compare the standardised regression coefficients, beta. According to the beta, Success and well-being theory is a far more powerful determinant of social trust than the voluntary organisation theory. But even though the beta is a standardised measure, you should use it with caution when the variables are not following the same scale. To get an extra argument for your conclusion, you could perform two bivariate regression analyses, one for each of the theories, and compare the amount of explained variance, R square.

The results also reveal that these two theories are far from the only sources of social trust. The overall explanatory power of the model is about 15 %. This is statistically significant (unlikely to have occurred purely by chance), but substantively it explains only a small part of the social basis of trust. But considering the type of data used here (categorical dependent variable with ten categories, data from many different countries), 15 % is a good result.

  1. Pick four countries. Perform a regression analysis similar to the one above for each of these countries. It is only necessary to use the design weight. SPSS

    Start by switching on the weight. Then select a country, as the syntax example does. Select your own country or, if you do not live in an ESS country, select Norway as in the following example (If you do not know which code each country has, go to Variable view in SPSS, and to the column "Values". Click on the cell for the "Country" variable. Then you will get a list of codes and countries.)

    WEIGHT BY dweight.
    USE ALL.
    COMPUTE filter_$=(Country = 18).
    VARIABLE LABEL filter_$ 'Country = 18 (FILTER)'.
    VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'.
    FORMAT filter_$ (f1.0).
    FILTER BY filter_$.
    EXECUTE .
     
    REGRESSION
    /MISSING LISTWISE
    /STATISTICS COEFF OUTS R ANOVA
    /CRITERIA=PIN(.05) POUT(.10)
    /NOORIGIN
    /DEPENDENT ppltrst
    /METHOD=ENTER ln_org fac_suc .
    FILTER OFF.
    USE ALL.
    EXECUTE.
    WEIGHT OFF.
    1. Do you find any differences between the four countries? If there is little difference between the countries, do you think you have found a universal social pattern? If there are differences between the countries, what sorts of factors might explain them?
    2. Are the results statistically significant? Are they substantively meaningful?
    3. Is the individual theory still a more powerful predictor than the social one?
    4. This question can't be solved using NSDstat: Experiment with different regression models, by putting the success and well-being variable into the equation first, followed by the voluntary organisation theory, and then switching the order. Use forward regression and backward regression. Does it make any difference to the results? If so, why do you think it makes a difference?
    5. What does the regression coefficient tell us about cause-and-effect relations?
    6. What do you think might be a better predictor of social trust?
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