Final answer:
To narrow a confidence interval without lowering confidence, a researcher should increase the sample size, which reduces the error bound of the interval.
Step-by-step explanation:
A researcher can reduce the width of a confidence interval without reducing her level of confidence primarily by increasing her sample size. Option 2, 'Increase her sample size,' is the correct answer. A larger sample size reduces the error bound and, therefore, narrows the confidence interval while maintaining the same level of confidence. It's not about using a smaller critical value or reducing the sample size, as both could affect the confidence level; meanwhile, increasing the power is a concept related to hypothesis testing which influences the likelihood of detecting an effect, not directly the width of a confidence interval.
In summary, the error bound decreases as the sample size increases, leading to a narrower interval. If the same level of confidence is maintained, this increased precision in the interval estimate comes without sacrificing confidence in our estimation.