A nurse researcher critiquing a research study notes that a confidence interval (CI) is too large for a new therapy to be clinically meaningful. What likely contributed to this statistical outcome?
A) Strong power level
B) Quantitative experimental design
C) Statistical analysis
D) Too small a sample

Question

Quizplus · Accepted Answer

A confidence interval (CI) is a range of values that is likely to contain the true population value with a certain level of confidence. The width of the CI is determined by several factors, including the sample size, the level of confidence, and the variability of the data.
If a nurse researcher critiquing a research study notes that a confidence interval (CI) is too large for a new therapy to be clinically meaningful, it suggests that the width of the CI is too broad and does not provide a precise estimate of the effect size. This is typically caused by having too small a sample size, which increases the variability of the data and decreases the precision of the estimate.
In other words, a larger sample size would likely provide a more precise estimate of the effect size and narrow the width of the CI, making it easier to determine whether the new therapy is clinically meaningful or not. Therefore, increasing the sample size is often recommended in such cases to improve the precision and accuracy of the estimate.

A Nurse Researcher Critiquing a Research Study Notes That a Confidence