Quiz 5 Flashcards
A method of measuring respondents’ attitudes from 0 to 100 is called a ______.
feeling thermometer
A relationship between a causal variable and a dependent variable within one value of another causal variable is known as a ______.
controlled effect
A researcher hypothesizes that individuals differ in support for a balanced budget amendment based upon their partisan affiliation. He controls for education level and finds that highly educated Democrats are twenty-seven points less likely to support a balanced budget amendment than highly educated Republicans, but Democrats with lower education are two points more likely to support a balanced budget than Republicans with lower education. What’s going on here?
an interaction between education and partisanship
A researcher hypothesizes that individuals differ in their support for free speech based upon partisanship. He controls for gender and finds that women are more supportive than men for both Democrats and Republicans. What’s going on here?
an additive relationship
A researcher is examining the effect of partisanship on attitudes about Congress while controlling for gender and finds no relationship between partisanship and attitudes at any value of gender. This means the relationship between partisanship and attitudes toward Congress is ______.
spurious
A researcher studies attitudes about involvement in foreign wars based upon individual partisanship while controlling for issue salience. She graphs the results on a line-graph and notices that the lines for salience and partisanship cross each other at a point on the chart. This indicates the presence of a(n) ______ relationship.
interactive
A researcher studying support for international institutions finds that Democrats are more likely to support such institutions than are Republicans. When she controls for income, she finds that individuals with higher incomes are about 12 points more supportive of international institutions regardless of party. This is an example of a(n) ______.
additive effect
A researcher studying support for international institutions finds that Democrats are more likely to support such institutions than are Republicans. When she controls for income, she finds no difference between Republicans and Democrats on support for international institutions. This is an example of a(n) ______.
spurious effect
A(n) ______ summarizes a relationship between two variables after accounting for a rival variable.
partial effect
If age and gender together help to explain attitudes regarding welfare policy, it indicates that a(n) ______ is present.
additive relationship
If the direction of the relationship between the independent variable and the dependent variable is not constant at all values of the control variable, it means the relationship is______.
interactive
If the direction of the relationship between the independent variable and the dependent variable changes at different values of a control variable, it indicates that a(n) ______ is present.
interactive relationship
In a study of partisanship and attitudes toward social welfare spending while controlling for gender a researcher finds that women are 15 points more likely than men to support social welfare spending. This is an example of ______.
the partial effect of gender
In political research, controlled effects are summarized by a(n) ______ relationship.
partial
The rule of direction for nominal relationships helps us identify ______.
interaction relationships
To determine the direction of a nominal relationship it is necessary to ______.
subtract the other values from the base category’s value
We are able to summarize a partial effect using one number when the relationship is ______.
additive
When graphing the relationship between an independent variable and a dependent variable, the independent variable should be on the ______.
horizontal axis
When the partial effect must be described separately for each category of a control variable what type of relationship exists?
interactive
Which of the following are especially useful for lending clarity and simplicity to controlled comparison relationships?
line charts
A controlled comparison design refers to any characteristic that varies across categories of an independent variable
False
A controlled cross-tabulation table demonstrates the relationship between one or more in dependent variables and the dependent variable.
True
A cross-tabulation analysis may be used with an ordinal independent variable and a nominal dependent variable.
True
A simple comparison of two variables provides a zero-order relationship.
True
A zero-order relationship summarized an overall relationship between variables.
True
All additive relationships are straightforward and have symmetrical quality
True
An outlier is a pretreatment variable that is related to both the treatment and the outcome.
False
An overall association between two variables that does not take into consideration other possible differences between the cases being studied is known as a zero-order relationship.
True
Cross-tabulation analysis may be used only when both variables are measured at the ordinal level.
False
Determining whether an independent variable is positively or negatively related to a dependent variable is done using the partial relationship or partial effect.
False
If there is a clear rival explanation, a controlled comparison design does not work well.
False
Interaction relationships are protean shape-shifters, assuming a variety of forms.
True
Matching methods attempt to replicate random assignment in an observational setting.
True
Rival explanations undermine researchers’ ability to evaluate the effect of the independent variable on the dependent variable.
True
When you’re analyzing how values of an interval-level variable vary among groups, you use a mean comparison table
True
