Between-Subjects Design Overview

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Questions and Answers

What is true about the between-subjects design?

  • Different participants are assigned to each condition. (correct)
  • It allows measurement of dependent variables across repeated trials.
  • Participants experience all levels of the independent variable.
  • The same group is used for each experimental treatment.

Which of the following independent variables is best measured using a between-subjects design?

  • Video condition
  • Classroom environment
  • Age (correct)
  • Teaching method

What does systematic variance refer to in the context of between-subjects designs?

  • Unexplained variance that affects all groups equally.
  • Variability in scores that can be attributed to treatment effects. (correct)
  • Differences in individual participant characteristics.
  • Random fluctuations in data due to chance.

What is non-systematic variance primarily associated with in an experimental setting?

<p>Participant differences unrelated to the treatment. (D)</p> Signup and view all the answers

How are independent measures designs characterized in terms of participant data?

<p>Each participant contributes only one score on the dependent variable. (B)</p> Signup and view all the answers

What is one advantage of using a between-subjects design?

<p>There is a reduced risk of carryover effects. (D)</p> Signup and view all the answers

In a statistical analysis context of between-subjects design, what does the F-ratio help determine?

<p>The ratio of systematic variance to non-systematic variance. (B)</p> Signup and view all the answers

Which consideration is crucial regarding participant attention span in a study using between-subjects design?

<p>Participants may lose attention if the experiment takes too long. (D)</p> Signup and view all the answers

What is a key disadvantage of using a between-subjects design?

<p>Different anchors might influence ratings (C)</p> Signup and view all the answers

Which statement best describes the comparison effect in within-subjects designs?

<p>It results in larger differences perceived across conditions. (A)</p> Signup and view all the answers

In which scenario should a researcher avoid using a between-subjects design?

<p>When participants are likely to compare their conditions (C)</p> Signup and view all the answers

What does the term 'systematic variance' refer to in the context of independent measures design?

<p>Variation attributed to differences in experimental conditions (D)</p> Signup and view all the answers

Which method is best for reducing the impact of carry-over effects?

<p>Implementing a between-subjects design (D)</p> Signup and view all the answers

What aspect of participant attention might affect outcomes in a study using independent measures design?

<p>Differences in awareness of task instructions (D)</p> Signup and view all the answers

How does ecological validity relate to between-subjects designs?

<p>It ensures that study results are representative of real-world scenarios. (B)</p> Signup and view all the answers

What does using a scaling method in a between-subjects design help to control?

<p>Inconsistent participant responses across conditions (B)</p> Signup and view all the answers

What is the significance of a large F-ratio in testing group differences?

<p>It reflects a significant treatment effect. (C)</p> Signup and view all the answers

Which factor is considered a systematic variance in variance analysis?

<p>Differences attributed to the independent variable. (B)</p> Signup and view all the answers

In a between-groups design, what does high within-group variance suggest?

<p>Difficulty in observing treatment effects. (B)</p> Signup and view all the answers

Which scenario would most likely yield a small F-ratio?

<p>Low between-group variance and high within-group variance. (D)</p> Signup and view all the answers

What does a single-factor analysis of variance (ANOVA) allow researchers to assess?

<p>The impact of one independent variable across several conditions. (A)</p> Signup and view all the answers

Which of the following is a common environmental variable that could confound results?

<p>Time of day during data collection. (A)</p> Signup and view all the answers

What is assignment bias in the context of independent measures designs?

<p>Differences in participant characteristics across groups. (C)</p> Signup and view all the answers

Which variance is considered non-systematic or error variance?

<p>Variability attributed to chance factors. (A)</p> Signup and view all the answers

To achieve valid comparisons in a between-groups design, what practice should researchers follow?

<p>Standardize experimental procedures across conditions. (D)</p> Signup and view all the answers

What is the effect of individual differences on the validity of experimental results?

<p>They introduce potential confounding variables. (A)</p> Signup and view all the answers

What type of design provides a stronger evidence of cause-and-effect relationships?

<p>Single-factor multiple-group design. (C)</p> Signup and view all the answers

In the context of analysis of variance, what does a positive F-ratio indicate?

<p>Large systematic variance compared to error variance. (D)</p> Signup and view all the answers

What should researchers aim for in a between-groups design to ensure effective treatment comparisons?

<p>Maximize between-group differences and minimize within-group differences. (C)</p> Signup and view all the answers

Flashcards

Between-Subjects Design

A research design where different groups of participants are assigned to different conditions of the independent variable.

Independent Variable (IV)

The variable that the researcher manipulates or changes to see its effect on the dependent variable.

Dependent Variable (DV)

The variable that is measured to see if it changes based on the independent variable.

Independent Measures

Different participants are used in different conditions or groups of a study.

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Participant Assignment

The process of placing participants into different conditions or groups within a study.

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Individual Differences

Variations in characteristics, such as age, personality, and background, among participants.

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Randomization

Assigning participants to conditions in a way that each individual has an equal chance of being placed in any group; helps minimize pre-existing differences between groups

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Internal Validity

The extent to which a study's results can be attributed to the manipulation of the independent variable and not to other factors.

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Within-subjects design

An experimental design where each participant is exposed to all conditions.

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Comparison effect

Increased perception of differences in conditions when participants experience multiple conditions.

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Carryover effect

Influence of one condition on the outcome of subsequent conditions.

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Anchoring bias

The tendency for individuals to use a starting point (anchor) to make judgments.

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Between-subjects anchoring issue

Groups using different anchors on a rating scale reduces comparability across conditions.

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Ecological validity

The extent to which the results of a study can be generalized to real-world settings.

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Threats to validity

Factors that may compromise the accuracy or generalizability of study results.

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F-ratio

A statistical measure that compares the variance between groups to the variance within groups. It indicates the effect of the independent variable on the dependent variable.

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Between-Group Variance

The variability between different groups in a study. It reflects the differences in the scores of participants in different treatment conditions.

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Within-Group Variance

The variability within each group in a study. It represents the differences in the scores of participants within the same treatment condition.

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Treatment Index

The F-ratio represents the treatment index, which reflects the presence or absence of treatment effects.

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Large Between-Group Variance

A large difference between the scores of participants in different groups. It suggests a strong effect of the independent variable.

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Large Within-Group Variance

A large difference in scores within the same group. It makes it difficult to see a clear effect of the independent variable.

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Small Between-Group Variance

A small difference between the scores of participants in different groups. It indicates a weak effect of the independent variable.

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Single-Factor Multiple-Group Design

A research design where different groups of participants are assigned to different levels of a single independent variable with multiple levels.

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Assignment Bias

When the groups in a study are not equivalent due to the way participants were assigned to conditions.

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Environmental Variables

Factors in the environment that can affect the dependent variable and potentially confound the results.

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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
  • 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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