Ch10 - Between-Subjects Factorial Designs

C. An independent variable

What is a factor in experimental research?

A. A dependent variable

B. A treatment outcome

C. An independent variable

D. A statistical interaction

B. More than one independent variable

What distinguishes a factorial design from a single-factor design?

A. More than one dependent variable

B. More than one independent variable

C. More participants

D. More statistical tests

D. A two-factor experiment

What is the simplest form of a factorial design?

A. A single-group design

B. A repeated-measures design

C. A correlational design

D. A two-factor experiment

A. Psychotherapy and antidepressant drugs

Which example best illustrates two independent variables in a factorial design?

A. Psychotherapy and antidepressant drugs

B. Depression score and anxiety score

C. Gender and depression

D. Treatment outcome and recovery

B. Depression

In the psychotherapy and antidepressant example, what is the dependent variable?

A. Type of therapy

B. Depression

C. Medication dosage

D. Session length

C. Both treatment effects and interaction effects

What type of information can factorial designs provide?

A. Only descriptive statistics

B. Only main effects

C. Both treatment effects and interaction effects

D. Only correlations

D. The effect of one IV on the DV

What is a main effect?

A. The effect of all IVs combined

B. The interaction of variables

C. Random variation

D. The effect of one IV on the DV

B. The number of independent variables

What determines how many main effects are possible in a factorial experiment?

A. The number of participants

B. The number of independent variables

C. The number of levels

D. The number of dependent variables

A. Exercise intensity reduces depression

Which of the following best represents a main effect in an exercise and depression study?

A. Exercise intensity reduces depression

B. Exercise works only for some durations

C. Exercise works differently for men and women

D. Exercise depends on therapy type

C. Statistical testing

How do researchers determine whether main effects exist?

A. Visual inspection of graphs

B. Comparing raw scores

C. Statistical testing

D. Increasing sample size

B. Three independent variables

In a 2 × 3 × 3 design, how many independent variables are present?

A. Two

B. Three

C. Six

D. Eighteen

D. Eighteen

In a 2 × 3 × 3 design, how many treatment conditions are there?

A. Six

B. Nine

C. Twelve

D. Eighteen

A. Gender, relationship, and severity

Which variables were independent variables in the sentencing study example?

A. Gender, relationship, and severity

B. Sentence length and severity

C. Age and sentence length

D. Depression and therapy type

C. Sentence length

What was the dependent variable in the child abuse sentencing study?

A. Severity of abuse

B. Gender

C. Sentence length

D. Relationship to the child

D. The joint effect of two or more IVs

What is an interaction?

A. The effect of one IV

B. A statistical error

C. A dependent variable

D. The joint effect of two or more IVs

B. When the effect of one IV changes across levels of another IV

When does an interaction occur?

A. When IVs have no effect

B. When the effect of one IV changes across levels of another IV

C. When sample size is small

D. When there is only one IV

A. Drug effectiveness varies by therapy condition

Which example demonstrates an interaction?

A. Drug effectiveness varies by therapy condition

B. Drugs always reduce depression

C. Therapy always works

D. Depression never changes

C. An interaction involving three or more IVs

What is a higher-order interaction?

A. A strong main effect

B. An interaction between two IVs

C. An interaction involving three or more IVs

D. A statistical assumption

D. Interpretation becomes difficult

Why are higher-order interactions challenging to interpret?

A. They are rare

B. They lack validity

C. They are invalid statistically

D. Interpretation becomes difficult

B. AB, AC, BC

Which of the following represents possible two-way interactions in a three-IV study?

A. ABC only

B. AB, AC, BC

C. A only

D. AB only

A. ABC

Which interaction represents a higher-order interaction in a three-IV study?

A. ABC

B. AB

C. AC

D. BC

C. It qualifies the interpretation of main effects

How does an interaction affect interpretation of results?

A. It eliminates main effects

B. It replaces statistical testing

C. It qualifies the interpretation of main effects

D. It simplifies conclusions

B. Both IVs must be considered together

Why must researchers consider all IVs when an interaction exists?

A. One IV becomes irrelevant

B. Both IVs must be considered together

C. Statistics cannot isolate effects

D. Sample size decreases

D. Listing factors in parentheses

What does the factor-labeling method involve?

A. Listing IV levels

B. Listing DV scores

C. Using graphs only

D. Listing factors in parentheses

A. 2 × 2 (Type of Name × Length of Name)

Which is an example of the factor-labeling method?

A. 2 × 2 (Type of Name × Length of Name)

B. 2 × 2 (Short, Long × Given, Nickname)

C. 2 × 2 (Scores × Means)

D. 2 × 2 (IV × DV)

C. Listing factors and their specific levels

What does the factor and levels method include?

A. Sample size

B. Statistical values

C. Listing factors and their specific levels

D. Only factor names

B. It provides more detailed information

What advantage does the factor and levels method have?

A. It reduces complexity

B. It provides more detailed information

C. It shortens notation

D. It removes interactions

A. It combines multiple one-factor experiments

Why is a factorial design more efficient than separate univariate experiments?

A. It combines multiple one-factor experiments

B. It reduces IVs

C. It avoids interactions

D. It removes variability

D. It better reflects real-world complexity

How do factorial designs improve external validity?

A. By increasing control

B. By reducing IVs

C. By eliminating confounds

D. By better reflecting real-world complexity

C. Practical limitations

Why should between-subjects factorial designs be kept simple?

A. Participants lose interest

B. Statistics cannot handle complexity

C. Practical limitations

D. Interactions are invalid

B. Number of subjects, time, and interpretability

Which factors limit the complexity of between-subjects designs?

A. Ethics and funding only

B. Number of subjects, time, and interpretability

C. Random assignment

D. Measurement error

D. A factorial design

A researcher studies the effects of therapy type and medication on depression scores. What type of design is being used?

A. Single-factor design

B. Correlational design

C. Repeated-measures design

D. A factorial design

B. Two

In a study examining exercise intensity and exercise duration on depression, how many factors are present?

A. One

B. Two

C. Three

D. Four

C. Depression score

In a psychotherapy and antidepressant study, which variable is the dependent variable?

A. Type of therapy

B. Medication type

C. Depression score

D. Treatment condition

A. A main effect of exercise intensity

If exercise intensity reduces depression regardless of duration, what does this demonstrate?

A. A main effect of exercise intensity

B. An interaction

C. A higher-order interaction

D. No treatment effect

D. An interaction

If medication effectiveness differs depending on whether patients receive CBT or are on a waiting list, what does this indicate?

A. A main effect of medication

B. A placebo effect

C. Random error

D. An interaction

B. The effect of one IV depends on the level of another IV

Why is the result in the previous question considered an interaction?

A. Only one IV affected the DV

B. The effect of one IV depends on the level of another IV

C. There was no statistical testing

D. The sample size was small

C. Three

A 2 × 3 × 3 study examining gender, relationship to the child, and abuse severity includes how many independent variables?

A. One

B. Two

C. Three

D. Eighteen

A. Eighteen

In the same 2 × 3 × 3 study, how many treatment conditions are created?

A. Eighteen

B. Nine

C. Six

D. Three

D. Sentence length

In the child abuse sentencing example, what is the dependent variable?

A. Gender of the perpetrator

B. Relationship to the child

C. Severity of abuse

D. Sentence length

B. A higher-order interaction

If gender, relationship to the child, and severity of abuse together influence sentence length, what is this effect called?

A. A main effect

B. A higher-order interaction

C. A two-way interaction

D. A confound

A. AB, AC, BC

In a study with three independent variables, which of the following lists all possible two-way interactions?

A. AB, AC, BC

B. ABC only

C. A only

D. AB only

C. ABC

Which interaction represents a three-way (higher-order) interaction?

A. AB

B. AC

C. ABC

D. BC

D. Main effects must be interpreted cautiously

Why must researchers be careful when interpreting main effects in the presence of an interaction?

A. Main effects become invalid

B. Statistics cannot detect effects

C. Sample size decreases

D. Main effects must be interpreted cautiously

B. Both IVs simultaneously

When an interaction exists, how should the independent variables be interpreted?

A. Separately

B. Both IVs simultaneously

C. One at a time

D. Ignoring the weaker IV

A. 2 × 2 (Type of Name × Length of Name)

Which notation correctly uses the factor-labeling method?

A. 2 × 2 (Type of Name × Length of Name)

B. 2 × 2 (Short, Long × Given, Nickname)

C. 2 × 2 (IV × DV)

D. 2 × 2 (Scores × Means)

D. 2 × 2 (Type of Name: given, nickname × Length of Name: short, long)

Which notation correctly uses the factor and levels method?

A. 2 × 2 (Type × Length)

B. 2 × 2 (Name × Size)

C. 2 × 2 (IV × DV)

D. 2 × 2 (Type of Name: given, nickname × Length of Name: short, long)

C. It provides more detailed information about the design

Why might a researcher prefer the factor and levels method over the factor-labeling method?

A. It shortens the notation

B. It reduces sample size

C. It provides more detailed information about the design

D. It eliminates interactions

A. Studying interactions between variables

Why is a factorial design superior to running multiple single-factor experiments?

A. Studying interactions between variables

B. Reducing statistical testing

C. Eliminating main effects

D. Simplifying interpretation

D. It better represents real-world complexity

How do factorial designs improve external validity?

A. By reducing variability

B. By limiting IVs

C. By increasing control only

D. It better represents real-world complexity

B. The number of subjects required

Which practical limitation most strongly restricts complex between-subjects factorial designs?

A. Ethical approval

B. The number of subjects required

C. Measurement reliability

D. Instrument sensitivity

C. Results become harder to interpret

Why can adding many factors to a between-subjects design be problematic?

A. It eliminates main effects

B. It increases internal validity

C. Results become harder to interpret

D. It simplifies data analysis

True

A factorial design always includes more than one independent variable.

False

There can only be one main effect in any experiment.

True

A two-factor experiment is the simplest type of factorial design.

False

Interactions make main effects easier to interpret.

True

A higher-order interaction involves three or more independent variables.

False

The factor-labeling method provides more detailed information than the factor and levels method.

True

Factorial designs can improve external validity by better representing real-world complexity.

True

In a factorial design, there can be as many main effects as there are independent variables.

False

An interaction occurs when two independent variables have identical effects on the dependent variable.

True

When an interaction is present, the effect of one independent variable depends on the level of another independent variable.

False

A 2 × 3 × 3 factorial design contains only two independent variables.

True

A higher-order interaction can make interpretation of results more difficult.

False

Factorial designs are less efficient than running multiple single-factor experiments.

True

Between-subjects factorial designs should be kept simple due to practical limitations such as sample size and interpretability.