Research Methods in Psychology: Causation, Control, and Validity

Research Methods in Psychology

Types of Variables

Understanding variables is fundamental in psychological research, as they represent the elements that can change or be manipulated in a study.

• Independent Variable: The variable that is manipulated by the researcher to observe its effect on the dependent variable.

• Dependent Variable: The variable that is measured to assess the effect of the independent variable.

• Confounding Variable: An extraneous variable that correlates with both the independent and dependent variables, potentially distorting the results.

• Extraneous Variable: Any variable other than the independent variable that could influence the outcome of the experiment.

Example: In a study examining the effect of sleep on memory, sleep duration is the independent variable, memory test scores are the dependent variable, and caffeine intake could be a confounding variable.

Causation and Causal Claims

Distinguishing between correlation and causation is essential for interpreting research findings accurately.

• Causation: Implies that one variable directly affects another.

• Criteria for Causality:

  1. Covariation: The cause and effect must occur together.

  2. Temporal Precedence: The cause must precede the effect in time.

  3. Elimination of Alternative Explanations: Other possible causes must be ruled out.

Example: To claim that sleep improves memory, researchers must show that increased sleep precedes improved memory scores and that other factors (e.g., stress, diet) are controlled.

Types of Validity

Validity refers to the accuracy and appropriateness of conclusions drawn from research.

• Internal Validity: The extent to which a study can establish a causal relationship between variables.

• External Validity: The extent to which findings can be generalized to other settings, populations, or times.

• Construct Validity: The degree to which a test measures what it claims to be measuring.

• Statistical Conclusion Validity: The extent to which statistical analyses support the conclusions about relationships among variables.

Example: A laboratory experiment with strict control over variables may have high internal validity but low external validity if the setting is artificial.

Threats to Validity

Identifying and addressing threats to validity is crucial for designing robust psychological research.

• Participant Effects: Changes in participants' behavior due to their awareness of being studied.

• Experimenter Effects: Bias introduced by the researcher's expectations or behavior.

• 7 Threats to Internal Validity (MIL SMITH):

  1. Maturation: Changes in participants over time.

  2. Instrumentation: Changes in measurement tools or procedures.

  3. Location: Variations in the research setting.

  4. Selection: Differences in participant characteristics.

  5. Mortality: Loss of participants during the study.

  6. History: Events occurring during the study that affect results.

  7. Testing: Effects of repeated testing on participants.

Example: If participants drop out of a long-term study, mortality becomes a threat to internal validity.

Summary Table: Types of Validity

Type of Validity	Description	Example
Internal Validity	Ability to establish causal relationships	Random assignment in experiments
External Validity	Generalizability of findings	Field studies with diverse samples
Construct Validity	Accuracy of measurement tools	Validated questionnaires
Statistical Conclusion Validity	Appropriateness of statistical analyses	Correct use of statistical tests

Additional info: The "MIL SMITH" mnemonic is commonly used to remember the seven threats to internal validity in experimental research.