Deck 5: Making Controlled Comparisons

Question 1

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______.

A) interactive
B) spuriousness
C) additive
D) nonexistent

Answer 1

A

Question 2

A method of measuring respondents' attitudes from 0 to 100 is called a ______.

A) Guttman scale
B) Likert-type scale
C) feeling thermometer
D) cross-tabulation

Answer 2

C

Question 3

To determine the direction of a nominal relationship it is necessary to ______.

A) subtract the other values from the base category's value
B) add the other values to the left-most column of a variable value
C) subtract the other values from the right-most column of a variable value
D) add the other values to the right-most column of a variable value

Answer 3

A

Question 4

When the partial effect must be described separately for each category of a control variable what type of relationship exists?

A) additive
B) interactive
C) spurious
D) zero-order

Question 5

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) ______.

A) additive effect
B) spurious effect
C) interactive effect
D) partial effect

Question 6

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 ______.

A) interactive
B) additive
C) zero-order
D) spurious

Question 7

The rule of direction for nominal relationships helps us identify ______.

A) spuriousness
B) additive relationships
C) zero-order relationships
D) interaction relationships

Question 8

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?

A) an additive relationship between education and partisanship
B) a spurious relationship between education and partisanship
C) a zero-order relationship between education and partisanship
D) an interaction between education and partisanship

Question 9

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.

A) additive
B) interactive
C) spurious
D) zero-order

Question 10

We are able to summarize a partial effect using one number when the relationship is ______.

A) additive
B) spurious
C) interactive
D) zero-order

Question 11

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.

A) additive relationship
B) spurious relationship
C) interactive relationship
D) zero-order relationship

Question 12

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 ______.

A) a zero-order relationship
B) the partial effect of gender
C) the normative effect of gender
D) the nominal effect of gender

Question 13

A relationship between a causal variable and a dependent variable within one value of another causal variable is known as a ______.

A) controlled effect
B) compared effect
C) compound effect
D) consistent effect

Question 14

A(n) ______ summarizes a relationship between two variables after accounting for a rival variable.

A) additive effect
B) spurious effect
C) partial effect
D) interactive effect

Question 15

If age and gender together help to explain attitudes regarding welfare policy, it indicates that a(n) ______ is present.

A) interactive relationship
B) zero-order relationship
C) spurious relationship
D) additive relationship

Question 16

When graphing the relationship between an independent variable and a dependent variable, the independent variable should be on the ______.

A) vertical axis
B) either axis
C) horizontal axis
D) it is omitted from the graph

Question 17

In political research, controlled effects are summarized by a(n) ______ relationship.

A) zero-order
B) additive
C) interactive
D) partial

Question 18

Which of the following are especially useful for lending clarity and simplicity to controlled comparison relationships?

A) bar graphs
B) line charts
C) pie charts
D) cone graphs

Question 19

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) ______.

A) additive effect
B) spurious effect
C) interactive effect
D) zero-order effect

Question 20

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?

A) interaction
B) spuriousness
C) an additive relationship
D) a zero-order relationship

Question 21

All additive relationships are straightforward and have symmetrical quality.

Question 22

If there is a clear rival explanation, a controlled comparison design does not work well.

Question 23

Cross-tabulation analysis may be used only when both variables are measured at the ordinal level.

Question 24

A cross-tabulation analysis may be used with an ordinal independent variable and a nominal dependent variable.

Question 25

A simple comparison of two variables provides a zero-order relationship.

Question 26

A controlled cross-tabulation table demonstrates the relationship between one or more in dependent variables and the dependent variable.

Question 27

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.

Question 28

Interaction relationships are protean shape-shifters, assuming a variety of forms.

Question 29

An outlier is a pretreatment variable that is related to both the treatment and the outcome.

Question 30

When you're analyzing how values of an interval-level variable vary among groups, you use a mean comparison table.

Question 31

Rival explanations undermine researchers' ability to evaluate the effect of the independent variable on the dependent variable.

Question 32

Determining whether an independent variable is positively or negatively related to a dependent variable is done using the partial relationship or partial effect.

Question 33

Matching methods attempt to replicate random assignment in an observational setting.

Question 34

A controlled comparison design refers to any characteristic that varies across categories of an independent variable.

Question 35

A zero-order relationship summarized an overall relationship between variables.