Chapter 7

Chapter 7: The Experimental Research Strategy

Goals of Experimental Research Strategy

• Main Goal: Establish a cause-and-effect relationship between two variables.

  • Experiment Definition: A true experiment demonstrates that changes in one variable (Independent Variable - IV) directly cause changes in another variable (Dependent Variable - DV).

  • Causality Check: Rules out coincidental relationships.

Four Basic Elements of Experiments

1. Manipulation

   • The researcher alters one variable to create treatment conditions.

2. Measurement

   • A second variable is measured among participants, producing scores based on treatment conditions.

3. Comparison

   • Scores from one treatment condition are compared with another condition.

4. Control

   • Other extraneous variables are controlled to avoid influencing the examined variables.

Basic Components of an Experimental Research Study

• Not specified in detail in this section but pertains to the infrastructure of conducting experiments effectively.

Terminology for the Experimental Research Strategy

• Independent Variable (IV): The manipulated variable with various treatment conditions.

• Treatment Condition: A specific situation defined by the IV.

• Levels: Different values of the IV used to define treatment conditions.

Dependent and Extraneous Variables

• Dependent Variable (DV): The variable measured to assess effects of changes in the IV.

• Extraneous Variables: All other variables in the study not classified as IVs or DVs.

Causation Issues

• Third Variable Problem: Establishes that two variables are related but may be influenced by an unidentified third variable which can cause a spurious relationship.

• Directionality Problem: Not all studies clarify which variable is the cause and which is the effect.

Controlling Nature

• Experiments must isolate examined variables from all other variables to clarify relationships and conclusions.

Basic Goals in Causal Relationships

1. Ensure the IV precedes the DV.

2. Validate that a specific variable is the cause of changes in another variable, ruling out extraneous variables.

Manipulation in Experiments

• Manipulation Process: Determines specific IV values and creates corresponding treatment conditions.

Relationship Directionality and Manipulation

• Manipulation helps in identifying the direction of the relationship between IV and DV.

  • Example: Ice-cream consumption rises with temperature, but temperature does not change due to ice-cream distribution.

Third-Variable Problem and Manipulation

• Manipulation helps control extraneous influences, like crime rates rising with temperature, showing no direct connection with ice-cream consumption.

Control Measures

• Control other variables to prevent contamination of observed relationships and eliminate confounding variables (those varying with IV and DV).

Confounding Variables

• A confounding variable can skew outcomes, causing misleading results by affecting the DV unintentionally.

Extraneous vs Confounding Variables

• An extraneous variable becomes confounding only if it influences the DV and varies systematically with the IV.

Techniques for Controlling Extraneous Variables

1. Holding Variables Constant: Ensures certain variables remain unchanged.

2. Matching Values: Ensures equal values across treatment conditions.

3. Randomization: Avoids systematic relationships by using random processes.

Comparing Methods of Control

• Goal: Ensure that differences in DV are caused solely by the IV, with no other variable influencing outcomes.

Advantages and Disadvantages of Control Methods

• Holding Constant & Matching: Requires additional effort and measurement; can limit external validity.

• Randomization: Controls multiple variables but may not succeed in balancing them effectively.

Experimental and Control Conditions

• Experimental Condition: Represents treatment conditions.

• Control Condition: Represents no-treatment conditions against which experimental conditions are compared.

Importance of Control Conditions

1. No-treatment Control Condition: Does not receive the treatment but is crucial for comparison.

2. Placebo Control Condition: A non-effective treatment to assess psychological effects; known as the placebo effect.

   • Distinction between outcome research (effectiveness) and process research (active components).

Manipulation Checks

• Measures the effect of IV directly; executed through explicit measurements or participant questionnaires.

• Important in varying situations such as participant manipulations, subtle manipulations, placebo controls, and simulations.

Simulation and Field Studies

• Simulation: Experimental conditions replicate natural environments.

  • Mundane Realism: Relates to real-life resemblance.

  • Experimental Realism: Refers to participant engagement.

• Field Study: Conducted in natural settings as perceived by subjects.

Advantages and Disadvantages of Simulation and Field Studies

• Advantages: Increase external validity by investigating real-life situations.

• Disadvantages: Risk of nature intruding, reducing control, potentially compromising internal validity.