According to Wikipedia, external validity is the validity of generalized inferences in research, generally based upon experiments as experimental validity. Put simply, it is the extent to which the outcomes of a research can be generalized to other situations and to other individuals. External validity is a crucial requirement in quantitative research.
It determines whether it is feasible to draw more general conclusions based on the model employed and data gathered, and whether results may be generalized to other samples, time periods and configurations.
Three Main Threats to External Validity in Quantitative Research Studies
Population validity means whether inferences could be drawn from an investigation of a given population. The queries examined concern, for instance, whether a connection between two variables also exists in the population as a whole and not only in the chosen sample. External validity is severely threatened, if biases or any other constraints appear in the accessible population. If the sample size is insufficient and/or the sample isn’t random, the estimates could possibly be worthless, simply because the sample may not faithfully mirror the whole population. In such instances generalizations should not be made to the target population.
Time validity exhibits the extent to which the outcomes of a specific study at a point in time could be generalized to other time periods. If structural adjustments to the associations between variables happen, the time validity of such research will be low.
Environmental validity signifies whether results could be generalized across settings. International generalizability is an example of a possible problem.
In qualitative research, generalizability is worried with whether the study results are transferable, i.e. could be extended to a broader context, have theoretical generalizability, empirical applicability, practical usefulness, constructive generalizability. Serious risks to the transferability of a qualitative research can happen as a result of selective plausibility. That is, if the investigator, for instance, is unable to reconnect the empirical findings of the research at hand to those of other cases and theories, and explain how the new proof improves the understanding of the research question. Deficiency of comparison between empirical findings and prior theoretical contributions may result in rather myopic conclusions and, even worst, a scholar may claim to have found something previously proven in other research projects.
In numerous research projects and research designs, there could be a “trade-off” between internal validity and external validity: When steps are taken to increase the possibility of higher degrees of internal validity, these actions could also restrict the generalizability of the studies. This scenario has led many investigators call for “ecologically valid” tests. By that they suggest that experimental procedures should mimic “real-world” conditions. They condemn the absence of ecological validity in numerous laboratory-based research projects with a focus on unnaturally manipulated and limited environments. External validity and ecological validity are tightly related in the sense that causal inferences based upon ecologically valid research designs usually enable higher degrees of generalizability compared to those attained in an artificially created lab environment.
Watch a video on Threats to External Validity
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