Factorial Designs in Psychology Research

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Questions and Answers

What is the main focus of factorial designs in research?

  • Understanding how multiple independent variables affect a dependent variable (correct)
  • Examining the relationship between one independent variable and one dependent variable
  • Analyzing the effects of external environments on psychological outcomes
  • Isolating individual factors that contribute to human behavior

Which of the following is NOT a type of factorial design?

  • Pure (between-groups) factorial
  • Within-subjects factorial
  • Cumulative factorial (correct)
  • Mixed-factorial

In factorial designs, what is an interaction effect?

  • The combined effect of two or more variables influencing the outcome (correct)
  • The random variation in results due to external factors
  • The ability to predict behavior based on individual variables
  • The independent effect of one variable on the outcome

What factor can significantly influence happiness according to researchers?

<p>A mix of genetics, environment, and internal state (B)</p> Signup and view all the answers

Which is a potential advantage of using factorial designs in research?

<p>They allow examination of interactions between variables (A)</p> Signup and view all the answers

What does it mean when two factors interact in a study?

<p>The effects of one factor depend on the levels of a second factor. (A)</p> Signup and view all the answers

Which of the following presentations is likely to show an interaction effect for study time?

<p>Screen presentation at self-regulated time. (A)</p> Signup and view all the answers

What can you infer about the mean exam score in regards to the mode of presentation?

<p>Mean exam scores differ significantly between modes of presentation. (D)</p> Signup and view all the answers

In a study where both factors show interaction, what is likely true about the mean scores?

<p>Mean scores may rise or fall depending on the combination of factors. (C)</p> Signup and view all the answers

What is a key advantage of using factorial designs in psychological research?

<p>They offer higher ecological validity. (D)</p> Signup and view all the answers

In a 2 x 2 factorial design, how many different conditions are there?

<p>4 conditions (A)</p> Signup and view all the answers

Which of the following best describes a 2 x 3 factorial design?

<p>Two independent variables, one with two levels and another with three levels. (C)</p> Signup and view all the answers

Which of the following factors was not mentioned in the example of factors contributing to a poor exam mark?

<p>Anxiety during the exam (D)</p> Signup and view all the answers

How can the effects of two factors be examined simultaneously?

<p>Through a factorial design. (A)</p> Signup and view all the answers

In the context of factorial designs, which statement is true regarding levels?

<p>Levels indicate variations within each independent variable. (A)</p> Signup and view all the answers

In a three-factor design, which combination is evaluated in addition to the main effects?

<p>Two-way interactions (C)</p> Signup and view all the answers

In the memory experiment described, which factor would be classified as a within-group factor?

<p>Types of words (C)</p> Signup and view all the answers

Which of the following describes a four-way interaction in an experiment?

<p>Evaluating how four different factors interact simultaneously (C)</p> Signup and view all the answers

Which group received no treatment in the described study design?

<p>Control group (C)</p> Signup and view all the answers

What is the main effect of Factor A in the described design?

<p>There is a significant main effect. (C)</p> Signup and view all the answers

What can be concluded about the interaction of factors A and B?

<p>The interaction is present between illumination and image content. (D)</p> Signup and view all the answers

What is a disadvantage of a pure factorial design as described?

<p>It may require many participants. (A)</p> Signup and view all the answers

In the context of the study, how does darkness affect children's anxiety levels?

<p>It increases anxiety levels especially with scary images. (D)</p> Signup and view all the answers

What does a significant AxB interaction suggest in the study's context?

<p>The effects of one factor depend on the level of the other factor. (D)</p> Signup and view all the answers

What results from the analysis of M values for Neutral and Scary images?

<p>Scary images produce significantly higher M values in the dark. (A)</p> Signup and view all the answers

What could be a confounding variable in this pure factorial design?

<p>Individual differences among participants. (B)</p> Signup and view all the answers

What was the average M value for ‘Light off’ with 'Scary images'?

<p>$114$ (A)</p> Signup and view all the answers

What was the main effect of Factor A in the scenario provided?

<p>No, there was no main effect. (A)</p> Signup and view all the answers

What was the main effect of Factor B in the experiment?

<p>There was a significant main effect. (D)</p> Signup and view all the answers

What conclusion can be drawn regarding the interaction between Factors A and B?

<p>No interaction effect was observed. (C)</p> Signup and view all the answers

In the example provided, what does the phrase 'depends on' indicate?

<p>The outcome is influenced by both factors. (C)</p> Signup and view all the answers

When should the presence of an interaction be considered during analysis?

<p>Before considering main effects. (C)</p> Signup and view all the answers

What would the M values indicate in the interpretation of results?

<p>Mean recall scores for different conditions. (A)</p> Signup and view all the answers

How is a main effect reported when there is no interaction present?

<p>It should be discussed alone. (C)</p> Signup and view all the answers

What does an M value of 20 indicate for recall happy under learning happy?

<p>The average recall score for that condition. (D)</p> Signup and view all the answers

What would indicate a significant main effect of Factor A on recall scores?

<p>Higher M values for learning happy compared to learning sad. (C)</p> Signup and view all the answers

Which statement is true regarding the learning conditions 'learn happy' and 'learn sad'?

<p>Both conditions produce the same recall scores. (C)</p> Signup and view all the answers

In analyzing Factor A's impact on recall scores when there's no interaction, what is inferred?

<p>Factor A has no independent effect on recall scores. (D)</p> Signup and view all the answers

What does 'd' represent in the results indicated?

<p>The difference in means between learning conditions. (D)</p> Signup and view all the answers

If a main effect is reported for Factor B, what implications does this have?

<p>Factor B significantly influences the outcome of recall scores. (B)</p> Signup and view all the answers

Which would be the proper approach to report results showing both main effects and interactions?

<p>Discuss main effects before interactions. (B)</p> Signup and view all the answers

Flashcards

Factorial design

A research design that examines the effects of two or more independent variables (factors) on a dependent variable.

Independent variable

A variable that is manipulated by the researcher to see its effect on another variable.

Dependent variable

A variable that is measured to observe the effect of an independent variable.

Main effect

The independent effect of one factor in a factorial design, taking the other factors as constant.

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Interaction effect

A combined effect of two or more independent variables, where the effect of one variable changes depending on the level of another variable.

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Two-way interaction

The interaction between two factors.

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Fixed Time

Study time is set and doesn't vary..

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Self-regulated

Study time is managed by the student.

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Presentation Type

How information is displayed (e.g., paper, screen).

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What is a Factorial Design?

A research design where multiple independent variables (IVs) are systematically manipulated to examine their individual and combined effects on a dependent variable.

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Why are Factorial Designs useful?

They allow researchers to study complex interactions between multiple factors influencing a phenomenon. This gives a more realistic picture of how things work in the real world.

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Representing Factorial Designs

Factorial designs can be represented using a matrix with rows and columns representing different levels of each IV. Each cell of the matrix represents a unique condition in the experiment.

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Interpreting Factorial Results

Analyzing factorial results helps researchers understand both 'main effects' (individual effects of each IV) and 'interaction effects' (combined effects of multiple IVs).

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What is a Main Effect?

The effect of a single independent variable (IV) on the dependent variable, while holding other IVs constant.

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What is an Interaction Effect?

The combined effect of two or more independent variables (IVs) on the dependent variable. The effect of one IV depends on the level of another.

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Example: 2 x 2 Factorial Design

A factorial design with two independent variables (IVs), each with two levels. It leads to four unique conditions for study.

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Example: 2 x 3 Factorial Design

A factorial design with two independent variables (IVs), one with two levels and the other with three levels. It leads to six unique conditions for study.

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Pure Factorial Design

A research design with two or more independent variables (factors) where each participant is assigned to only one condition, combining levels of all factors.

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Factor A

The first independent variable in a factorial design.

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Factor B

The second independent variable in a factorial design.

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Between-Subjects Design

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

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Confounding Variable

An uncontrolled variable that can influence the dependent variable, making it difficult to isolate the effect of the independent variable.

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Disadvantages of Factorial Design

Factorial designs can require many participants and individual differences can become confounding variables.

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Between-S Factor

A factor in a factorial design where different groups of participants are assigned to different levels of the factor.

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Within-S Factor

A factor in a factorial design where the same participants experience all levels of the factor.

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Three-Way Interaction

The combined effect of three factors, where the relationship between two factors changes depending on the level of the third factor.

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Four-Way Interaction

The combined effect of four factors, showing how the relationship between three factors changes depending on the level of the fourth factor.

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No interaction

When two factors have independent effects, meaning the effect of one factor does not change depending on the level of the other factor.

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Interaction present

When two factors have a combined effect, meaning the effect of one factor changes depending on the level of the other factor.

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How to interpret results with interaction

When discussing results, consider the interaction effect before or at the same time as main effects. When reporting an interaction, use the phrase "depends on."

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How to interpret results without interaction

Discuss the main effects independently, as the interaction effect is absent.

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Interpret the results

Analyze the effects of different factors on the dependent variable, considering both main effects and interaction effects.

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When a main effect is present

There is a significant difference in the mean scores of the dependent variable across the levels of a factor, indicating a consistent effect of the factor.

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When a main effect is absent

There is no significant difference in the mean scores of the dependent variable across the levels of a factor, indicating no consistent effect of the factor.

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Why interaction can obscure main effects

The presence of an interaction can make it difficult to identify the true effect of each factor individually.

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"Depends on" phrase

When reporting an interaction, use phrases like "depends on" to indicate that the effect of one factor changes depending on the level of another factor.

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Levels of a factor

The different values or conditions of an independent variable in a factorial design.

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Mean score

The average score of the dependent variable across all participants in a given condition or level of a factor.

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Study Notes

PSYCH 306: Research Methods in Psychology - Factorial Designs

  • Factorial designs examine the relationships among multiple independent variables (IVs) and one dependent variable (DV) in a single study. This contrasts with simpler studies focusing on one IV at a time.

  • Examples of factorial designs include a 2x2 design, a 2x3 design, and more complex 3x2x2 designs.

  • A factorial design determines:

    • The main effects for each independent variable.
    • Interactions between independent variables.

Exam Schedule and Course Requirements

  • The final exam is scheduled for December 9th, from 6:30 PM to 9:30 PM.

  • The exam will consist of multiple-choice questions. Approximately 60 questions are anticipated.

  • The exam material covers lectures and readings since the last exam.

  • Homework assignment HW3 will be graded over the next two weeks.

  • Extra credit can be earned for participation in SONA.

  • The final grade is based on Exam 1 (37%), Exam 2 (37%), and Homework (26%). Specific point values for each homework assignment are available.

Types of Factorial Designs

  • Pure factorial designs (between-subjects):All Independent Variables (IVs) are between subjects. Groups of participants are randomly assigned to different treatment conditions.

  • Within-subjects factorial design:A single group of participants experiences all the conditions of the independent variables (IVs) in a certain order.

  • Mixed factorial designs:A factorial design combining both between-subjects (or independent-groups) and within-subjects conditions. This is useful when one independent variable is suited as a between-subjects procedure and the other as a within-subjects procedure.

Higher-order Factorial Designs

  • Higher-order factorial designs involve three or more factors.

  • Complex interactions between the factors increase in complexity.

Factorial Designs and Interactions

  • An interaction exists when the effect of one IV depends on the level of a second IV.
  • Non-parallel lines on a graph depicting the results of the study often indicate an interaction.

Structure of a Two-Factor Experiment

  • A 2x2 factorial design could have a Presentation Type (On Paper/On Screen) and Study Time (Fixed/Self-Regulated) as the two independent variables.

  • The row and column arrangement of an experiment are dictated by these independent variable levels.

Two-Factor Design

  • A two-factor design can be represented as a matrix, where each cell in the matrix represents a combinations of the factors (IVs).
  • The data provides the researcher with information about the individual and combined effects of the two factors.

Advantages of Factorial Designs

  • Highly efficient: They investigate the effects of multiple factors simultaneously, and can help replicate and expand existing studies in a single study.
  • Increased external validity: Inclusions of participant characteristics as a variable results in a more varied representation of participants in the study.
  • Enables examining interactions, which are crucial in many settings. This happens when the effect of one variable depends on the level of another variable.

Disadvantages of Factorial Designs

  • Can be more complex to interpret: Interactions between different independent variables can be hard to assess.
  • Increased chance for confounds: More factors make it harder to control for extraneous/unintentional variables.
  • May increase the number of participants needed.

Statistical Analysis of Factorial Designs

  • Statistical analysis often involves ANOVA, to analyze and test the significance of the mean differences observed across different treatment conditions.

  • The methodology used will vary based on whether the factors being analyzed are between or within subjects, and could be mixed.

Types of Interactions

  • Two-way interactions occur between all pairs of factors.
  • Three-way interactions occur between all three factors.
  • Similar patterns exist for more factors.

Interpreting Results

  • Look for main effects (the individual effects of each IV) first.
  • Assess the differences in row and column means.
  • Interactions: Examine how differences in row or column means change, across the groups of the different IV pairs or more.
  • If an interaction exists, the effect of one IV "depends" on the level of other IVs.
  • If no interaction, interpret main effects separately.

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