In: Statistics and Probability
The essential difference between internal and external validity is that internal validity refers to the structure of a study and its variables while external validity relates to how universal the results are.
Better internal validity often comes at the expense of external
validity (and vice versa). The type of study you choose reflects
the priorities of your research.Trade-off example
A causal relationship can be tested in an artificial lab setting or
in the ‘real world’. A lab setting ensures higher internal validity
because external influences can be minimized. However, the external
validity diminishes because a lab environment is different than the
‘outside world’ (that does have external influencing factors).A
solution to this trade-off is to conduct the research first in a
controlled (artificial) environment to establish the existence of a
causal relationship, followed by a field experiment to analyze if
the results hold in the real world.
Internal validity is not a s"yes or no" type of concept. Instead, we consider how confident we can be with the findings of a study, based on whether it avoids traps that may make the findings questionable.The less chance there is for "confounding" in a study, the higher the internal validity and the more confident we can be in the findings. Confounding refers to a situation in which other factors come into play that confuses the outcome of a study. For instance, a study might make us unsure as to whether we can trust that we have identified the above "cause-and-effect" scenario.In short, you can only be confident that your study is internally valid if you can rule out alternative explanations for your findings. As a brief summary, you can only assume cause-and-effect when you meet the following three criteria in your study:
The cause preceded the effect in terms of time.
The cause and effect vary together.
There are no other likely explanations for this relationship that
you have observed.