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

1 / 14

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

Cross-Tabulation Analysis; Making Comparisons; Controlled Comparisons June 2, 2008. Ivan Katchanovski , Ph.D. POL 242Y-Y. Cross-Tabulation. Cross-tabulation: A method of hypotheses testing Very common Very simple Bivariate analysis

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

## PowerPoint Slideshow about 'Cross-Tabulation Analysis; Making Comparisons; Controlled Comparisons June 2, 2008' - reya

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

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

Ivan Katchanovski, Ph.D.

POL 242Y-Y

Cross-Tabulation
• 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
Example: Cross-tabulation
• 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
Example: Cross-tabulation

Source: 1996 Lipset/Meltz survey

Example: Cross-tabulation
• 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.
Graphical Illustration

Source: 1996 Lipset/Meltz survey

Controlled Comparisons
• 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)

Example: Spurious Relationship

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

Spurious Relationship: Line Graph

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

Example: Interactive Relationship

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

Interactive Relationship: Line Graph

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

Exercise

Political party preference, 2006 Canadian Election Study Survey, %