1. Bivariate Regression
Vote 08
Vote 04

2. Bivariate Regression
Liberalism
Vote 08

3. Trivariate Regression
Liberalism
Vote 08
Vote 04

4. Crosstab: Liberalism and Presidential Vote
1.00 Extremely conservative
2.00 Conservative
3.00 Slightly conservative
4.00 Moderate
5.00 Slightly liberal
6.00 Liberal
7.00 Extremely liberal
1. John McCain
95.4%
74.1%
63.0%
41.2%
17.2%
15.0%
1.2%
2. Barack Obama
4.6%
25.9%
37.0%
58.8%
82.8%
85.0%
98.8%
Total
100.0%

5. Correlation: Liberalism and Presidential Vote

6. Bivariate Regression: Liberalism and Presidential Vote

7. Crosstab: Presidential Vote (2004) and Presidential Vote (2008)
Bush
Kerry
1. John McCain
80.9%
7.5%
2. Barack Obama
19.1%
92.5%
Total
100.0%

8. Correlation: Presidential Vote (2004) and Presidential Vote (2008)

9. Bivariate Regression: Vote 04 and Presidential Vote

10. Crosstab: Presidential Vote (2004) and Presidential Vote (2008), controlling for liberalism
Bush
Kerry
Conservative
1. John McCain
89.4%
16.2%
2. Barack Obama
10.6%
83.8%
Total
100.0%
Moderate
59.3%
15.6%
40.7%
84.4%
Liberal
51.7%
3.6%
48.3%
96.4%

11. Correlation: Presidential Vote (2004) and Presidential Vote (2008), controlling for liberalism

12. Crosstab: Presidential Vote (2008) and Liberalism, controlling for Presidential Vote (2004)
1.00 Conservative
2.00 Moderate
3.00 Liberal
1. John McCain
89.4%
59.3%
51.7%
2. Barack Obama
10.6%
40.7%
48.3%
Total
100.0%
16.2%
15.6%
3.6%
83.8%
84.4%
96.4%
100.0% 

13. Correlation: Presidential Vote (2008) and Liberalism, controlling for Presidential Vote (2004)

14. Correlations

15. Explaining Venn Diagrams
Variance
Vote 08

16. Explaining Venn Diagrams
Variance
Vote 04

17. Explaining Venn Diagrams
Variance
Liberalism

18. Plot showing positive covariance
Mean urban %
Mean female literacy

19. Plot showing negative covariance
Mean calorie intake
Mean infant mortality

20. Plot showing no covariance
Mean GDP
Mean crop production

21. Pearson r = .62 Pearson r = .73 Pearson r = .61 Vote 04 Liberalism

22. Vote 08
Vote 04
Liberalism

23. Multivariate Regression: Presidential Vote (2008), controlling for Liberalism and Presidential Vote (2004)

24. Appendix: Syntax
The following set of commands changes a nominal variable into an ordinal variable. Prespref_2004 had six categories for their presidential preference, including Nader and others. I needed a variable that just included Bush and Kerry.
if prespref_2004 = 1 presvote_2004 = 1.
if prespref_2004 = 2 presvote_2004 = 2.
execute.
I wanted a variable that went in the same direction as presvote_2004 and presvote so I recoded ideology to make liberalism coded high.
recode ideology (7=1) (6=2) (5=3) (4=4) (3=5) (2=6) (1=7) into liberalism.
Here I am adding value labels for liberalism.
add value labels liberalism 1 'Extremely conservative' 2 'Conservative' 3 'Slightly conservative'
4 'Moderate' 5 'Slightly liberal' 6 'Liberal' 7 'Extremely liberal' .
Here I am creating a three category variable for libealism so the crosstab is easier to understand.
recode liberalism (1=1) (2=1) (3=1) (4=2) (5=3) (6=3) (7=3) into liberalismc.
add value labels liberalismc 1 'Conservative' 2 'Moderate' 3 'Liberal' .
Here I am running a crosstab with presidential vote as the dependent variable and liberalism as the independent variable.
crosstabs tables = presvote by liberalism/cells = col /stats = corr.
Here I am running a crosstab with presidential vote as the dependent variable and 2004 vote as the independent variable.
crosstabs tables = presvote by presvote_2004/cells = col count/stats = corr.
Here I am running a correlation between the three variables.
corr presvote presvote_2004 liberalism.
Here I am running a crosstab with presidential vote as the dependent variable and 2004 vote as the independent variable, controlling for liberalism.
crosstabs tables = presvote by presvote_2004 by liberalismc/cells = col /stats = corr.
Here I am running a crosstab with presidential vote as the dependent variable and liberalism as the independent variable, controlling for 2004 vote.
crosstabs tables = presvote by liberalismc by presvote_2004/cells = col /stats = corr.
Here I am running a regression with presidential vote as the dependent variable and liberalism and vote 04 as the independent variables.
regr vars = presvote presvote_2004 liberalism / depe = presvote/enter.