In social research, if one relies on a single piece of data, there’s the danger that undetected error in the data-production process may render the analysis incorrect.
If, on the other hand, diverse kinds of data lead to the same conclusion, you can be a little more confident in that conclusion. (If 2 points cross, you can be more confident that your boat’s going in the right direction.)
What’s involved in triangulation is not just a matter of checking whether inferences are valid but of discovering which inferences are valid.
Don’t take any data at face value. And don’t regard some data as true and some as false.
Use multiple methods if your research requires it. And use data-analysis approaches like triangulation if it fits. But just use triangulation consistently within one perspective - without drawing from different methodological perspectives.
Triangulation constitutes the first phase of analysis; it’s used to estimate the error inherent in quantitative measurements. It also serves as a building block for the incorporation of qualitative data. Sequential mixed method:
QUANT > TRIANGULATION > QUAL (to deepen the analysis of quantitative findings)