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13 Cards in this Set

  • Front
  • Back
Reasons for utilizing multivariate techniques
1)Gathering additional information about a specific bivariate relationship by using another variable.
2)Multivariate statistical techniques cannot prove causation, but can provide evidence.
Z variable
Third variable that is controlled to see the relationship between X and Y.
If the control variable has an effect, the relationship between X and Y will change under various conditions of Z.
Partial Tables
Tables that are split according to the categories of the Z variable.
This controls for the effect of Z.
A more detailed form of multivariate analysis.
Level of measurement for multivariate analysis
Nominal and ordinal
Direct Relationships
The relationship between X and Y are the same in all partial tables and the bivariate tables.
Spurious or intervening relationships
The relationship between X and Y is the same in all partial tables, but much weaker than in the bivariate table.
Each partial table and the bivariate table show different relationships between X and Y.
Outcome of a Direct Relationship
Z has no effect on the relationship between X and Y and can be ignored.
Outcome of a Spurious Relationship
Z occurs before both X and Y in time and is a common cause of both X and Y.
Ignore X and focus on Y and Z.
Outcome of an Intervening Relationship
X is causally linked to Z which is causally linked to Y
Continue to analyze all three variables.
Outcome of an Interaction
Incorporate Z and analyze Z's subgroups separately.
Partial Gamma
Strength of Association between X and Y once Z has been removed