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Questions and Answers
What must researchers consider when testing participants on multiple dependent variables?
What must researchers consider when testing participants on multiple dependent variables?
Why is a manipulation check essential in experiments with multiple dependent variables?
Why is a manipulation check essential in experiments with multiple dependent variables?
In a factorial design, what does it mean when the effect of one independent variable depends on the level of another independent variable?
In a factorial design, what does it mean when the effect of one independent variable depends on the level of another independent variable?
What is the main drawback of a multifactorial design in psychological experiments?
What is the main drawback of a multifactorial design in psychological experiments?
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What should researchers do to ensure internal consistency among multiple measures of the same construct?
What should researchers do to ensure internal consistency among multiple measures of the same construct?
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What is a main effect in a factorial design?
What is a main effect in a factorial design?
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In a study examining cell phone use and time of day, which of the following best describes the interaction?
In a study examining cell phone use and time of day, which of the following best describes the interaction?
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Which statistical technique is used to group variables into clusters in psychological research?
Which statistical technique is used to group variables into clusters in psychological research?
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Which of the following describes what a factorial design with non-manipulated independent variables is equivalent to?
Which of the following describes what a factorial design with non-manipulated independent variables is equivalent to?
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What does multiple regression analyze?
What does multiple regression analyze?
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Which of the following is a common dependent variable in correlational studies assessing mood and self-esteem?
Which of the following is a common dependent variable in correlational studies assessing mood and self-esteem?
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What is the primary focus of examining relationships among multiple variables?
What is the primary focus of examining relationships among multiple variables?
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Which of the following is an example of a psychological factor derived from measurements?
Which of the following is an example of a psychological factor derived from measurements?
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What is the main characteristic of a between-subjects variable?
What is the main characteristic of a between-subjects variable?
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Which of the following describes a within-subjects variable?
Which of the following describes a within-subjects variable?
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What does a mixed factorial design involve?
What does a mixed factorial design involve?
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What is a significant limitation of non-manipulated independent variables?
What is a significant limitation of non-manipulated independent variables?
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Which of the following is an example of assigning participants in a mixed-factorial design?
Which of the following is an example of assigning participants in a mixed-factorial design?
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In a study measuring memory with a non-manipulated independent variable, which group would typically not be randomized?
In a study measuring memory with a non-manipulated independent variable, which group would typically not be randomized?
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Which design allows for assessing the effects of a therapy type while also considering participant gender?
Which design allows for assessing the effects of a therapy type while also considering participant gender?
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Why is it important to measure a non-manipulated variable like hypochondriasis in a memory test?
Why is it important to measure a non-manipulated variable like hypochondriasis in a memory test?
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Study Notes
Complex Research Designs
- Psychologists often observe the effects of an independent variable (IV) on multiple dependent variables (DVs).
- This can lead to carryover effects from testing participants through multiple DVs.
- Manipulation checks are necessary when constructs are manipulated indirectly (e.g., emotions, internal states).
- Researchers need to ascertain if their manipulation was effective.
- Multiple measures of the same construct are used in some studies. This strategy employs self-report along with physiological measurements for examining the effects, e.g., exercise on stress.
- In multi-response measures of stress, each separate item on a rating scale can be treated as a separate DV, but it's better to use a multi-response measure of the construct, (e.g., stress).
- Assess internal consistency using Cronbach's alpha to ensure test items correlate with each other.
Multiple Independent Variables
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Factorial design enables researchers to investigate whether the effect of one independent variable depends on the level of another.
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An independent variable is also known as a factor.
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To understand the interaction between factors, examine how the different levels of each factor depend on each level of the other factor (i.e., consider all possible combinations).
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Factorial designs can have multiple independent variables (e.g., two, three, or more).
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A 2 x 2 design means two independent variables, each with two levels, resulting in four experimental conditions.
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Similarly, a 2 x 3 design involves two independent variables, with one having two levels and the other three. This creates six conditions.
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Examples include treatment (e.g., behavior modification, psychotherapy), dosage (e.g., 100 mg, 300 mg), and treatment setting (e.g., inpatient, day treatment, outpatient).
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It's unusual to have designs with more than three factors, each with more than two or three levels. These designs can swiftly become unwieldy.
Assigning Participants to Conditions
- Researchers must choose whether to treat factors as between-subjects or within-subjects variables.
- For between-subjects variables, participants are assigned to only one condition of an independent variable.
- For within-subjects variables, participants are assigned to every condition or level of an independent variable.
- Mixed factorial designs are possible where researchers use both between-subjects and within-subjects variables.
Non-manipulated Independent Variables
- Factors that aren't manipulated but are instead measured can be treated as between-subjects factors.
- But note that no causal conclusions can necessarily be drawn from non-manipulated factors (versus manipulated ones).
- An example involves a study examining memory for health-related words and non-health related words, with participants divided based on self-reported levels of hypochondriasis.
- Non-manipulated independent variables can play an important but not causal or experimental role.
Graphing Results of Factorial Experiments
- Two key results to analyze in factorial designs are main effects and interactions.
- A main effect represents the influence of one independent variable averaged across all levels of the other independent variables.
- An interaction happens when the effect of one factor depends on the level of another.
Correlational Studies with Factorial Designs
- Factorial designs can be used in correlational studies to understand relationships among variables.
- Researchers might use variables like mood and self-esteem as independent variables to understand their relationship with something like the willingness to have unprotected sex (the dependent variable).
Assessing Relationships Among Multiple Variables
- Analyzing the associations among multiple variables, both categorical and quantitative, is a key aspect of research.
- Factor analysis is a technique that creates clusters or groups of variables based on their shared relationships. This is used to reduce many variables into underlying factors.
Examples of Psychological Measurements
- Examples of measurement factors include mathematical intelligence, verbal intelligence, and big five factors.
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Description
This quiz explores complex research designs used in psychology, focusing on the interaction of independent and dependent variables. Learn about manipulation checks, multi-response measures, and the significance of internal consistency using Cronbach's alpha. Ideal for understanding advanced research methodologies.
