"A threat to external validity is an explanation of how you might be wrong in making a generalization."[4] Generally, generalizability is limited when the cause (i.e. the independent variable) depends on other factors; therefore, all threats to external validity interact with the independent variable.
The ability to apply findings to other populations
External validity refers to the extent to which research findings can be generalized to settings, populations, and times beyond the study conditions. To determine external validity, researchers can assess the representativeness of the sample used in the study compared to the broader population, evaluate the ecological validity by examining if the study conditions reflect real-world scenarios, and consider whether the results hold true across different contexts or populations. Additionally, replication of the study in diverse settings can help confirm the generalizability of the findings.
Internal validity has to do with the accuracy of the results. Results could be inaccurate if samples are not selected randomly. External validity has to do with the generalizability of the findings to the population. If the sample selected is only Hispanics under the age of 25, then it would be hard to generalize the results to the entire US population.
for Gate exam there is a validity but i think for pgeset there is no validity.
Regression threats refer to factors that can compromise the validity of regression analysis results, often leading to incorrect conclusions about the relationships between variables. Common threats include omitted variable bias, where important predictors are left out, multicollinearity among independent variables, and measurement errors in the data. These issues can distort the estimated relationships, making it essential for researchers to carefully consider and address them during analysis. Proper model specification and diagnostic tests can help mitigate these threats.
The main threats to validity are bias, confounding and chance. But keep in mind the internal and the external validity. Internal validity is the extent to which systematic error is minimised during the stages of data collection. where as the external validity encompasses the extent to which the results of the trials provide a correct basis for generalisation.
If you gain internal validity do you lose external validity
examples of internal and external validity
There are a number of ways to reduce threats to validity:By arguing against the threatBy observing and measuring the threat.By analysisBy preventive actionBy design.
No it is not easier because of the external flow.
The difference between internal and external validity is in their nature. Internal validity indicates if a study depicts relation between two variables. External validity on the other hand generalizes the study of the variables.
Yes. Internal validity is whether or not the experiment is studying what it intends to. External validity is whether or not the study can be generalised outside of the study. For example, if you had a perfect experiment set up, that measures something perfectly, then it will have internal validity. You haven't, however, shown that you would get the same results in different cultures, or in different time periods. Thus the experiment may not have external validity.
By ruling out a series of threats to that validity. Please see the link for a list of them.
Some examples of threats to validity that could impact the results of this study include selection bias, measurement error, confounding variables, and researcher bias.
External validity is the extent that results from a study generalize to other people, places, and situations--how well the findings stand outside the study and the extent to which they can be replicated. The internal validity is that extent to which the study's design enables it to measure and study what it intends to study.
The type of validity concerned with whether findings can be generalized to other groups or settings is called external validity. It assesses the extent to which research results can be applied beyond the specific conditions or population studied. High external validity indicates that the findings are applicable to a broader context, whereas low external validity suggests limitations in generalizability.
Internal validity is the degree to which the results are attributable to the independent variable and not some other explanations.External validity is the extent to which the results of a study can be generalized.