2| Validity, Types of Validity, Threats to Internal Validity

Validity

• refers to how well a study measures what it intends to measure

• determines whether the research findings are accurate, trustworthy, and applicable to real-world situations

Internal Validity

• The extent to which a study accurately establishes a cause-and-effect relationship between the independent variable (IV) and dependent variable (DV), without interference from confounding variables.

• The higher this is means stronger confidence that the IV caused the observed changes in the DV.

External Validity

The degree to which the study’s findings can be generalized to other populations, settings, or time periods.

Population Validity

Refers to how well the results apply to different groups of people beyond the sample used in the study.

Ecological Validity

Refers to how well the study reflects real-world settings and behavior.

Construct Validity

• The extent to which the study accurately measures theoretical concepts (constructs) it claims to investigate.

• The higher this is means the variables used truly represent the psychological concept being studied.

Temporal Validity

• The extent to which research findings remain valid over time.

• If a study’s results only apply to a specific era and are not relevant today, it has low ___________

Selection Bias

• It occurs when there’s a non-random selection of participants, leading to an unrepresentative sample.

• Solutions: 

  • Use random sampling or random assignment to ensure participants are evenly distributed across conditions.

  • Conduct a pre-test to assess any pre-existing differences between groups.

History Bias

• External events that occur during the experiment can affect participants’ behavior.

• Solutions: 

  • Conduct experiments in a controlled environment to minimize external influences.

  • Use control groups that are not exposed to the event.

Maturation Bias

• Changes in participants over time that aren’t related to the experimental treatment but affect the outcome.

• Solutions: 

  • Use a control group to compare if changes are related to the treatment.

  • Keep the duration of the experiment short to minimize maturation effects.

Testing Effect

• Participants may change their behavior due to familiarity with the test or procedure.

• Solutions: 

  • Use counterbalancing to vary the order of conditions.

  • Pre-test participants but make sure the test is not repeated too often.

Instrumentation Bias

• Changes in measurement tools or procedures that affect the outcome of the study.

• Solutions: 

  • Use consistent measurement tools throughout the study.

  • Ensure standardized procedures are followed for all participants.

Regression to the Mean

• When participants are selected based on extreme scores, they tend to return to more average levels in subsequent measurements.

• Solutions: 

  • Avoid selecting participants based solely on extreme scores.

  • Use random assignment to ensure more accurate representation of the population.

Experimental Mortality

• “Attrition Bias”

• Occurs when participants drop out of the study, leading to potential bias if the dropouts differ from those who remain.

• Solution: 

  • Minimize dropout rates by monitoring participant wellbeing.

  • Use intention-to-treat analysis to account for dropouts in the final analysis.

Demand Characteristics

• When participants alter their behavior due to their perceptions of what the experimenter expects.

• Solutions: 

  • Deception (if ethically appropriate) to reduce participants' expectations.

  • Ensure participants are blinded to the true purpose of the study.

Experimenter’s Bias

• When the researcher’s expectations or beliefs unintentionally influence the participants or the outcome of the study.

• Solutions: 

  • Double-blind procedures to prevent the researcher’s expectations from influencing results.

  • Ensure clear, objective criteria for data collection.