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What is true about the between-subjects design?
What is true about the between-subjects design?
Which of the following independent variables is best measured using a between-subjects design?
Which of the following independent variables is best measured using a between-subjects design?
What does systematic variance refer to in the context of between-subjects designs?
What does systematic variance refer to in the context of between-subjects designs?
What is non-systematic variance primarily associated with in an experimental setting?
What is non-systematic variance primarily associated with in an experimental setting?
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How are independent measures designs characterized in terms of participant data?
How are independent measures designs characterized in terms of participant data?
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What is one advantage of using a between-subjects design?
What is one advantage of using a between-subjects design?
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In a statistical analysis context of between-subjects design, what does the F-ratio help determine?
In a statistical analysis context of between-subjects design, what does the F-ratio help determine?
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Which consideration is crucial regarding participant attention span in a study using between-subjects design?
Which consideration is crucial regarding participant attention span in a study using between-subjects design?
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What is a key disadvantage of using a between-subjects design?
What is a key disadvantage of using a between-subjects design?
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Which statement best describes the comparison effect in within-subjects designs?
Which statement best describes the comparison effect in within-subjects designs?
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In which scenario should a researcher avoid using a between-subjects design?
In which scenario should a researcher avoid using a between-subjects design?
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What does the term 'systematic variance' refer to in the context of independent measures design?
What does the term 'systematic variance' refer to in the context of independent measures design?
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Which method is best for reducing the impact of carry-over effects?
Which method is best for reducing the impact of carry-over effects?
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What aspect of participant attention might affect outcomes in a study using independent measures design?
What aspect of participant attention might affect outcomes in a study using independent measures design?
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How does ecological validity relate to between-subjects designs?
How does ecological validity relate to between-subjects designs?
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What does using a scaling method in a between-subjects design help to control?
What does using a scaling method in a between-subjects design help to control?
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What is the significance of a large F-ratio in testing group differences?
What is the significance of a large F-ratio in testing group differences?
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Which factor is considered a systematic variance in variance analysis?
Which factor is considered a systematic variance in variance analysis?
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In a between-groups design, what does high within-group variance suggest?
In a between-groups design, what does high within-group variance suggest?
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Which scenario would most likely yield a small F-ratio?
Which scenario would most likely yield a small F-ratio?
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What does a single-factor analysis of variance (ANOVA) allow researchers to assess?
What does a single-factor analysis of variance (ANOVA) allow researchers to assess?
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Which of the following is a common environmental variable that could confound results?
Which of the following is a common environmental variable that could confound results?
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What is assignment bias in the context of independent measures designs?
What is assignment bias in the context of independent measures designs?
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Which variance is considered non-systematic or error variance?
Which variance is considered non-systematic or error variance?
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To achieve valid comparisons in a between-groups design, what practice should researchers follow?
To achieve valid comparisons in a between-groups design, what practice should researchers follow?
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What is the effect of individual differences on the validity of experimental results?
What is the effect of individual differences on the validity of experimental results?
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What type of design provides a stronger evidence of cause-and-effect relationships?
What type of design provides a stronger evidence of cause-and-effect relationships?
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In the context of analysis of variance, what does a positive F-ratio indicate?
In the context of analysis of variance, what does a positive F-ratio indicate?
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What should researchers aim for in a between-groups design to ensure effective treatment comparisons?
What should researchers aim for in a between-groups design to ensure effective treatment comparisons?
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Study Notes
Between-Subjects Design
- A different group of participants is assigned to each condition
- Each group receives a different experimental treatment and the groups are compared
- The key element is using separate groups of participants for different conditions
- Data from the dependent variable (DV) is compared across groups to identify differences
- Each participant experiences only one level of the independent variable (IV)
- This design is also called an independent-measures experimental design
- Some independent variables can only be measured in between-subjects designs (ex: age, gender)
- Other independent variables can be measured in either between-subject or within-subject designs (ex: teaching method, video condition)
Outline of Between-Subjects Design
- Between-subjects design (also called between-groups or independent groups design)
- Systematic and non-systematic variance
- The F-ratio
- Confounding variables
- Individual differences
- Environmental variables
- Randomization
- Additional threats to internal validity
- Advantages and disadvantages
Systematic Variance
- Between-subjects (systematic) variance refers to differences in means among different treatment groups
- These differences can be due to treatment effects or errors due to chance.
Non-Systematic Variance
- Within-group (non-systematic) variance refers to differences in scores of participants in a given treatment group.
- It is due only to chance factors (random variability)
- It should thus be minimized to ensure the reliability of the results
Testing Group Differences
- Between-group and within-group variance is used to calculate an index called the F-ratio
- A large between-group variance is desirable
- A large within-group variance is undesirable as it makes it harder to see an effect
Why Between-Subjects Designs Are Popular
- Carryover effects are of unknown duration, and thus using separate subjects avoids any interactions between the conditions
- One can estimate the bias introduced by carryover effects
Disadvantages of Between-Subjects Designs
- Often requires many participants
- Recruitment can be challenging for specific populations (ex. postpartum depression)
- Individual differences and environmental differences can impact the results
- Generalizing findings can be difficult due to holding extraneous variables constant, reducing real-world applicability of the study
- Experimenter-expectancy and subject-expectancy biases can be avoided through blinding participants and experimenters to condition assignments
- Additionally, the data analyst can be blinded to participant conditions.
Threats to Internal Validity
- Attrition
- Participants dropping out of a study is a threat if it happens at different rates across groups.
- Communication between groups
- Treatment effects may spread between conditions or there can be different expectations between groups (ex. resentment), causing differences between groups unrelated to the treatment
Matching
- Matching is used to control for participant characteristics
- Pair participants with similar characteristics before assigning them to different conditions of the study.
- Matching can be extended to comparing groups in blocks instead of just pairs.
- Matching involves some specific steps to ensure meaningful comparability.
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Description
This quiz focuses on the between-subjects design in experimental research, highlighting its key elements and characteristics. It discusses how different groups of participants are assigned to varying experimental conditions and the importance of comparing data across these groups. Explore the advantages and challenges associated with this independent-measures experimental design.
