What defines internal validity in experimental designs?

What defines internal validity in experimental designs?

• A. It is the extent to which observed effects are due to the manipulated variable rather than confounds.
• B. It is the consistency of measurements across repeated trials.
• C. It is the representativeness of the sample to the population.
• D. It is the size of the observed effect.

Answer: (A)

Internal validity is about whether the study’s observed effects can be truly attributed to the manipulated variable rather than to other confounding factors. When internal validity is high, we can make a causal claim that changes in the outcome were caused by the experimental manipulation, because potential confounds have been controlled or ruled out. That’s why the best description is the extent to which observed effects arise from the manipulated variable rather than confounds. To support this, researchers use techniques like random assignment, appropriate control groups, consistent procedures, and, when possible, blinding to minimize alternative explanations such as history, maturation, selection biases, instrumentation changes, or demand characteristics. In contrast, reliability asks about the consistency of measurements across trials, external validity concerns generalizability to other settings or populations, and effect size gauges how large the observed effect is. So the core idea is causal attribution within the study, ensured by controlling confounding influences.

Internal validity is about whether the study’s observed effects can be truly attributed to the manipulated variable rather than to other confounding factors. When internal validity is high, we can make a causal claim that changes in the outcome were caused by the experimental manipulation, because potential confounds have been controlled or ruled out. That’s why the best description is the extent to which observed effects arise from the manipulated variable rather than confounds. To support this, researchers use techniques like random assignment, appropriate control groups, consistent procedures, and, when possible, blinding to minimize alternative explanations such as history, maturation, selection biases, instrumentation changes, or demand characteristics. In contrast, reliability asks about the consistency of measurements across trials, external validity concerns generalizability to other settings or populations, and effect size gauges how large the observed effect is. So the core idea is causal attribution within the study, ensured by controlling confounding influences.