Exercise 7: Attitude on Gun Control and the Presidential Vote
Step A. Create and interpret Table 7A
Another reason for introducing a control variable into the analysis is to see if the relationship between the independent and dependent variable is stronger for some groups of people than it is for others. If we find that such is the case, we commonly refer to that as a conditional relationship. An example of a conditional relationship involves the association between attitudes toward gun control and the presidential vote. Clinton and Trump differed in their positions on gun control, with Clinton favoring stricter gun control laws and Trump opposing them. These differences reflected typical differences between the parties on this issue. If voters cast their ballots on the basis of this issue, at least in part, then we would expect voters who favored tougher gun control laws to be more likely to vote for Clinton. To see if this is so, create Table 7A, a two-variable table that examines the relationship between attitude on gun control (K16) and presidential vote (A02). To simplify the table, use the recoded version of A02 that excludes the minor party voters, as you have in previous exercises.
If you ran Table 7A as suggested, you should have a table with two columns and two rows. Attitude on gun control (the independent variable) should be on the top of the table (the column variable), and the two-party presidential vote (the dependent variable) should be on the side of the table (the row variable). Percentages should be calculated by column (i.e., they should sum to 100% for each column). In reading your table, take care to properly interpret the percentages, remembering that they are column percentages, not row percentages.
You should attempt to answer these questions to see if you are able to correctly read the table and interpret the data:
- What percentage of voters who favored stronger gun control laws voted for Clinton? What percentage of those opposed did so? The difference between these two percentages is one indicator of the strength of the relationship between these two variables.
- Note that we could also use the difference between the percentage of those favoring stronger gun control laws and those opposing them who cast a ballot for Trump. The difference between these two percentages is the same as the difference obtained by using the percentages for Clinton, since we are using the two-party presidential vote. Either way, there is about a 54 point difference.
Step B. Create and interpret Table 7B
Table 7A shows that overall there is a strong relationship between attitude on gun control and the presidential vote. This does not mean that all groups of voters were equally influenced by this issue. We can hypothesize about the types of voters for whom this relationship would be stronger and the types for whom it would be weaker. One possible hypothesis is that the relationship will be stronger for those who think that it is an issue of high importance. Those who do not think that this is a very important issue should be less likely to vote on the basis of gun control. You can test this hypothesis by introducing issue importance as a control variable (K17) into the analysis when you create Table 7B.
If you ran Table 7B as suggested, you should have a table that consists of four subtables. Each subtable should have two columns and two rows. Each subtables should have attitude on gun control (the independent variable) on the top of the table (the column variable), and the two-party presidential vote (the dependent variable) on the side of the table (the row variable). Percentages should be calculated by column (i.e., they should sum to 100% for each column). There should be one subtable for each category of issue importance, from extremely important to not important. In reading your subtables, take care to properly interpret the percentages, remembering that they are column percentages, not row percentages.
You should attempt to answer these questions to see if you are able to correctly read the table and interpret the data:
- What is the relationship between attitude toward gun control and presidential vote among those who think that this is an extremely important issue? What is the relationship among those who think that it is not an important issue? What is the relationship among those who are between these two extremes? Be sure to focus on the strength of the relationship in each subtable.
- How does the relationship between the attitude and presidential vote in each subtable compare to the original relationship in Table 7A? What conclusion do you draw from this?
In this example, there is a relationship between the attitude toward gun control and presidential vote in each subtable, but the strength of the relationship varies. In the first subtable, there is over a 70 point difference in voting for Clinton between those in favor of stronger gun control and those opposed to it; in the last subtable, the difference is about 20 points. Clearly, the strength of the relationship increases as the importance of the issue increases.
In this example, our original two-variable relationship becomes somewhat stronger among voters who thought that it was an extremely important issue and considerably weaker among those who did not think that the issue was important. In all four subtables, those who oppose stronger gun control laws are more likely to vote for Trump than are those who favor them, but the extent of the difference is the greatest among voters who place a very high importance on the issue and the least among voters who place a low importance on the issue. Therefore issue importance is a conditional variable in this situation, as we hypothesized.
From this analysis, we might generalize and conclude that specific issues will have a greater effect on the vote for those who think the issue is important. That then might lead us to think about who is most likely to be concerned about any given issue. While the survey did not directly ask about issue importance for most issues, we might infer this from other characteristics, such as demographic or social attributes.