Controlling Extraneous Variables in Experimental Research

Controlling Extraneous Variables

• Controlling extraneous variables is crucial for establishing a clear causal relationship between the independent variable (IV) and dependent variable (DV).
• Confounding occurs when an extraneous variable systematically changes across experimental conditions, affecting the IV-DV relationship.

Extraneous Variables

• Definition: Any variable that is not being investigated but can potentially affect the DV.
• The goal is to control these variables to accurately compare responses between the control and experimental groups.
• Four types of extraneous variables:
  • Physical variables
  • Social variables
  • Personality variables
  • Context variables

Physical Variables

• Definition: Aspects of the testing situation that need to be controlled (physical conditions of the experiment).
• Examples:
  • Day of the week
  • Experimental room environment
  • Distractions
  • Lighting

Regulating Physical Variables:

1. Elimination

• Completely removes the extraneous physical variable.
• Example: Soundproofing to remove noise.
• This prevents the variable from affecting treatment conditions differently.

2. Constancy of Conditions

• Keeps all aspects of the treatment conditions identical, except for the IV.
• Example: Testing all subjects in the same room at the same time of day, using the same stimuli

3. Balancing

• Equally distributes the effects of the extraneous variable across treatment conditions.
• Example: Running half of the subjects in each condition in the morning and half in the evening.
• Useful in pretest-posttest designs.

Prioritizing Techniques

1. Eliminate extraneous variables whenever possible.
2. Keep conditions constant when elimination is not possible.
3. Balance the effects of extraneous variables when constancy is not possible.

Social Variables

• Definition: Aspects of the relationships between subjects and experimenters that can influence experimental results.
• Includes demand characteristics and experimenter bias.

1. Demand Characteristics

• Definition: Cues within the experimental situation that elicit specific participant responses.
• These can be behavioral or verbal cues.
• Participants might alter their behavior based on the perceived purpose of the experiment.
• Demand characteristics can confound an experiment if they vary across experimental conditions.

Managing Demand Characteristics

• Provide clear and concise instructions.
• Use a single-blind experiment.
  • Subjects are not told their treatment condition.
  • This eliminates cues that might alter their behavior.
• Address deception carefully with thorough debriefing and informed consent.
• Placebo Effect:
  • When a subject receives a passive treatment and improves because of positive expectancies.
• Cover Story:
  • A false but plausible explanation of the experimental procedures to disguise the research hypothesis.
  • Should be used cautiously and ethically.

2. Experimenter Bias

• Definition: Any behavior by the experimenter that can confound the experiment.
• Example: Providing more attention to subjects in one condition than another.
• Rosenthal Effect (Pygmalion effect):
  • Experimenters treat subjects differently based on their expectations, influencing subject performance.
  • Teachers might give more attention to high-aptitude students.

Managing Experimenter Bias

• Use a double-blind design.
  • Both the experimenters and subjects are blinded to the conditions.
  • Controls both demand characteristics and experimenter bias.
  • Single-blind experiments only control demand characteristics by blinding the subjects.

Personality Variables

• Experimenter's personality can affect experimental results.
• Warm and friendly experimenters may get better results than hostile ones.

Managing Personality Variables

1. Employ multiple experimenters, assigning an equal number of subjects to each.
   • Apply the principle of balancing.
2. Treat the experimenter as an independent variable in statistical analysis.
   • If an interaction is found, the experiment is confounded.
3. Minimize face-to-face contact and closely follow a script.
4. Video tape sessions to confirm consistent performance.

Context Variables

• Definition: Extraneous variables produced by experimental procedures or the research setting.
• Includes how participants are assigned to conditions.

Subject Selection

• Allowing subjects to self-select experiments based on appealing titles can lead to a biased sample.
• Example: Recruiting for "a memory test experiment" vs. "a heavy metal music experiment."
• Avoid running experiments on friends, as this can bias the sample and threaten external validity.