Internal validity, unlike external and construct validity, deals with causal relationships. In other words, the question is whether any additional research that is found is actually associated with the study that is being conducted. The question, again, is whether we can be confident that the outcome of the study is a result of the experiment itself. What this means is that internal validity is the extent to which a change in a given variable is caused by the change in another variable.
According to Jimenez-Buedo (2011), it is difficult to make a valid reference that there is a causal relationship when conducting an experiment in a laboratory-style setting. Jimenez-Buedo (2011) also ...view middle of the document...
(2012), you must use a robust definition of validity. What this appears to mean is that you must be able to be certain that the study you are conducting stands up to the strictest definition of validity and can stand up to such factors as confirmatory factor analysis, for example, to confirm the validity of the results.
Threats to External and Construct Validity
According to Wijnhaven and Bloemen (2014), there are five threats to external validity that include the following:
1. Makeup of the sample unit such as gender and education level of the sample and how it relates to the causal relationship i.e. (the sample may not match the needs of the study and may therefore impair the causal relationship)
2. How the sample is treated—for example, whether there is some form of remuneration for participation in the study
3. Findings from a given study cannot be effectively inferred to other studies and different outcomes
4. Observations may be biased based on times, settings or persons that are not generalizable to other situations
5. Causal relationships can’t be explained across other settings
According to this same source, Wijnhoven and Bloemen (2014), one of the biggest concerns regarding demographic information is whether the information can be trusted if it is self-provided. ...