> Triangulation can help to increase the validity/credibility of research
> findings from qualitative research studies. Collecting and analyzing data
> from multiple sources or through multiple approaches can help us reduce any
> bias inherent in one particular source or approach. For example, if a main
> finding from one approach is completely absent or unsupported by data from
> another approach, the finding may have been shaped by the researcher’s bias
> or it may have been a random occurrence with no significance.
>  Following this logic, the main benefit of conducting triangulation is to
> reduce the likelihood of false alarm, or falsely identifying something that
> really doesn’t exist. This would then seem to be the exact opposite of what
> sample size increase can do for a statistical test, which is to reduce the
> likelihood of missing something that actually does exist. What do you
> think? Or is there a different way to characterize the function of
> triangulation? [250 words, 2 refeences, 2 In Text Citations. Original
> ScholarlyWriting Only. No ESL please]

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