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Questions and Answers
What type of factor is represented by the subject variable in a PxE mixed factorial design?
What type of factor is represented by the subject variable in a PxE mixed factorial design?
- Between-subject factor (correct)
- Both between-subject and within-subject factor
- Within-subject factor
- Neither factor
Under what condition should a simple effects analysis be conducted?
Under what condition should a simple effects analysis be conducted?
- When the main effects are statistically significant
- When the interaction effect is statistically significant (correct)
- When sample size is adequate
- When the interaction effect is not statistically significant
Which of the following comparisons is NOT appropriate in a simple effects analysis?
Which of the following comparisons is NOT appropriate in a simple effects analysis?
- Condition 2 and 4
- Condition 1 and 2
- Condition 3 and 4
- Condition 1 and 4 (correct)
What is the primary purpose of conducting a simple effects analysis after a significant interaction is found?
What is the primary purpose of conducting a simple effects analysis after a significant interaction is found?
In a PxE mixed factorial design, which components are included?
In a PxE mixed factorial design, which components are included?
What does a factorial design allow researchers to do compared to single-factor designs?
What does a factorial design allow researchers to do compared to single-factor designs?
In a 2 x 2 x 4 factorial design, how many conditions or cells are created?
In a 2 x 2 x 4 factorial design, how many conditions or cells are created?
Which statistical test is generally used to analyze the main effects and interaction effects in a factorial design?
Which statistical test is generally used to analyze the main effects and interaction effects in a factorial design?
What happens to levels and conditions in factorial designs compared to single-factor designs?
What happens to levels and conditions in factorial designs compared to single-factor designs?
What does a main effect represent in the context of factorial designs?
What does a main effect represent in the context of factorial designs?
How are interaction effects defined in factorial designs?
How are interaction effects defined in factorial designs?
What is the first step to determine the number of conditions in a factorial experiment?
What is the first step to determine the number of conditions in a factorial experiment?
What kind of design incorporates multiple independent variables and their levels?
What kind of design incorporates multiple independent variables and their levels?
What is the term used to describe the overall inferential stats performed in ANOVA?
What is the term used to describe the overall inferential stats performed in ANOVA?
Which interaction effect would be considered the most significant if found in an ANOVA with three independent variables?
Which interaction effect would be considered the most significant if found in an ANOVA with three independent variables?
What issue arises when two or more conditions show means that are near the maximum in a graph?
What issue arises when two or more conditions show means that are near the maximum in a graph?
What is indicated when the answer to which yields higher grades is 'it depends'?
What is indicated when the answer to which yields higher grades is 'it depends'?
In a mixed factorial design, how are independent variables categorized?
In a mixed factorial design, how are independent variables categorized?
Which type of graph is commonly used to represent data in factorial designs?
Which type of graph is commonly used to represent data in factorial designs?
How can you determine if there is an interaction effect from a graph?
How can you determine if there is an interaction effect from a graph?
What additional control problems must be addressed in a mixed factorial design?
What additional control problems must be addressed in a mixed factorial design?
What statistical method is recommended to assess the significance of main and interaction effects?
What statistical method is recommended to assess the significance of main and interaction effects?
What distinguishes a PxE factorial design?
What distinguishes a PxE factorial design?
What is a characteristic of a completely within-subject factorial design?
What is a characteristic of a completely within-subject factorial design?
When analyzing recall strategies, what is a main effect observed?
When analyzing recall strategies, what is a main effect observed?
Which of the following effects cannot occur in an ANOVA analysis?
Which of the following effects cannot occur in an ANOVA analysis?
What does the interaction effect demonstrate in the example of recall strategies?
What does the interaction effect demonstrate in the example of recall strategies?
What is a characteristic of main effects compared to interaction effects?
What is a characteristic of main effects compared to interaction effects?
What can you infer if you find that the recall was higher with the 4 sec rate than the 2 sec rate?
What can you infer if you find that the recall was higher with the 4 sec rate than the 2 sec rate?
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Study Notes
Factorial Design
- Factorial designs investigate the interaction of independent variables.
- Notation: Number of digits = number of independent variables, each digit represents the number of levels for that IV.
- Example: 3 x 5 factorial has 2 IVs, one with 3 levels and the other with 5.
- Conditions: The number of conditions equals the product of the numbers in the notation.
- Example: 2 x 4 = 8 conditions
Analyzing Factorial Designs
- Main effect: The overall effect of one IV, ignoring the other IVs.
- Example: Examining the effect of "Memorization Type" by combining data across levels of "Presentation Rate".
- Interaction effect: When the effect of one IV depends on the level of another IV.
- Example: Higher grades in "Science" may depend on whether it's a "lab" or "lecture" course.
- Data Representation: Use a matrix to organize data and a line graph to visualize.
- Non-parallel lines in a graph suggest an interaction.
- Statistical Analysis:
- Use ANOVA (Analysis of Variance) to test for significance.
- Each effect (main and interaction) is tested using an "F-test".
- Example: In a 2 IV design, the ANOVA tests for A, B, and AxB.
Varieties of Factorial Designs
- Mixed Factorial: At least one IV is between-subjects and at least one is within-subjects.
- Control Challenges: Handling equivalent groups for between-subjects and order effects for within-subjects.
- PxE Factorial: Both a manipulated IV and a subject IV.
- Example: Studying the effect of "environment" (manipulated IV) on groups with different "personalities" (subject IV).
- PxE Mixed Factorial: Combines the two above.
- Between-subjects IV (subject variable), within-subjects IV (manipulated variable).
Simple Effects Analysis
- Purpose: Analyze interaction effects in more detail.
- When: Performed if the interaction effect is statistically significant.
- Method: Examines the effect of each IV at different levels of the other IV.
- Example: Comparing "color conditions" at different "alcohol dosages".
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