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Cross-Tabulation Analysis; Making Comparisons; Controlled Comparisons June 2, 2008PowerPoint Presentation

Cross-Tabulation Analysis; Making Comparisons; Controlled Comparisons June 2, 2008

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Cross-Tabulation Analysis; Making Comparisons; Controlled Comparisons June 2, 2008

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Cross-Tabulation Analysis; Making Comparisons; Controlled Comparisons June 2, 2008

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Cross-Tabulation Analysis; Making Comparisons; Controlled Comparisons June 2, 2008

Ivan Katchanovski, Ph.D.

POL 242Y-Y

- Cross-tabulation: A method of hypotheses testing
- Very common
- Very simple
- Bivariate analysis
- Appropriate for nominal, ordinal, and interval-ratio variables

- Bivariate table of percentages
- The dependent variable is in rows
- The independent variable is in columns
- Percentage totals are column totals

- Research hypothesis: Canadians are more supportive of equality than Americans are
- The dependent variable: Preference for equality
- in rows

- The independent variable: Country
- in columns

Table 1. Preference for freedom and equality in the US and Canada, percent

Source: 1996 Lipset/Meltz survey

- Comparison:
- compare percentages across columns at the same value of the dependent variable
- Look for significant differences:
- A rule of thumb for survey data: 4% or more in expected direction

- Example from Table 1:
- 44% of Canadians, compared to 33% of Americans, prefer equality over freedom

- Interpretation of results:
- The cross-tabulation analysis supports the research hypothesis.

Figure 1. Preference for freedom and equality in the US and Canada, percent

Source: 1996 Lipset/Meltz survey

- Analysis of the relationship between and independent variable and a dependent variable controlling for another variable
- Types of relationships
- Additive: Control variable adds to explanation of an dependent variable by an independent variable
- Spurious: Relationship between an independent variable and a dependent variable disappears when a control variable is introduced
- Interactive: Relationship between an independent variable and a dependent variable depends on the value of control variable

Table 2. Preference for freedom and equality in the US and Canada controlling for gender, % (fictional data)

Figure 2. Preference for equality in the US and Canada controlling for gender, % (fictional data)

Table 3. Preference for freedom and equality in the US and Canada controlling for religiosity, % (fictional data)

Figure 3. Preference for equality in the US and Canada controlling for religiosity, % (fictional data)

Table 4. Preference for freedom and equality in the US and Canada controlling for race, % (fictional data)

Figure 4. Preference for equality in the US and Canada controlling for race, % (fictional data)

Political party preference, 2006 Canadian Election Study Survey, %