Validity talks about the soundness of the research design and methods. While carrying out the experiment, the researcher has two objectives, relating to the validity, i.e. draw conclusions about the impact of an independent variable on the group under study and make inferences about the population as a whole. The first objective stresses on internal validity, whereas the second focuses on external validity.
The basic difference between internal and external validity is that the former talks about the relationship between variables whereas the latter is concerned with the universality of the results. To further comprehend the topic, check out this article.
Content: Internal Validity Vs External Validity
Comparison Chart
| Basis for Comparison | Internal Validity | External Validity |
|---|---|---|
| Meaning | Internal validity is the extent to which the experiment is free from errors and any difference in measurement is due to independent variable and nothing else. | External validity is the extent to which the research results can be inferred to world at large. |
| Concerned with | Control | Naturalness |
| What is it? | It is a measure of accuracy of the experiment. | It checks whether the casual relationship discovered in the experiment can be generalized or not. |
| Identifies | How strong the research methods are? | Can the outcome of the research be applied to the real world? |
| Describes | Degree to which the conclusion is warranted. | Degree to which the study is warranted to generalize the result to other context. |
| Used to | Address or eliminate alternative explanation for the result. | Generalize the outcome. |
Definition of Internal Validity
In statistics, internal validity is used to mean the measure of accuracy, which checks the soundness of the experiment, specifically regarding confounding. It gauges whether the independent variables cause the observed effects on the dependent variables or not. When observed effects are under the influence of or confounded by extraneous variable, then it would be difficult to draw valid conclusions, about the relationship between variables.
Simply, internal validity refers to the degree to which cause and effect relationship based on the experiment is warranted, ascertained by the extent to which the experiment avoids systematic errors.
High internal validity allows the researcher to choose one explanation over the other with enough confidence, as it ignores confounds. The less the confounding in an experiment, the higher is its internal validity.
Definition of External Validity
The term external validity implies the determination of whether the casual relationship observed in the study can be generalized or not. It ascertains, Can the results obtained through the experiment be generalized to other situations and if so, to what settings, groups of people, times it can be extrapolated?
External Validity identifies the correctness of the research findings, by examining its applicability from one setting to another. Threats to external validity take place when the specific set of research conditions does not practically consider the interactions of other variables of the real world.
The two types of external validity, which measures the strength of the research are:
- Population validity
- Ecological validity
Key Differences Between Internal and External Validity
The points presented to you describe the differences between internal and external validity:
Conclusion
An experimental design is expected to have both internal and external validity. Internal validity is the most important requirement, which must be present in an experiment before any inferences about treatment effects are drawn. To establish internal validity, extraneous validity should be controlled. On the other hand, external validity is the cornerstone of a good experiment design and is a bit difficult achieve.
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