Another way is to do member checking. After gathering information from your study and analyzing it, it is good to check with the participants to see if they agree with you. Can the members validate what you said? If the members of the study think that you are on the right track then the researcher can feel good that they are drawing the proper conclusions.
Is there a pattern in your data and observations? If there is, then that can be seen as a way to validate your data. Triangulation is possible if the data frequently points to the same conclusions.
Before a study a researcher tries to predict the outcome of research or what the study is hoping to find or reinforce. But the results might point to something else. If it appears often enough, then this 'rigor' points to another conclusion. The researcher did not initially expect this result but it has been found often enough to now be deemed important.
The researcher should look at this closely and see why an unexpected pattern occurred. There may have been a flaw in the methodology. There could be an unexpected result that requires more attention and analysis. The researcher should step back and try to explain why an unexpected result occurred. This could help the researcher find a new insight.
Validation is important so that the researcher can feel confident that their study is an accurate picture of the world around them. If the study is an accurate portrayal of the results that came from their research then it might provide insights that are useful and practical.