Recent years have seen a heightened interest in estimating effect size - a common measure of effect magnitude in biomedical research - because of its direct clinical relevance. In this article, three interval estimates of effect size for randomized comparative parallel-group studies with unequal variances are discussed. Two real-life examples illustrate that confidence intervals obtained by three methods are quite different, especially when the sample sizes are small. Simulation results show that confidence intervals generated by the modified signed log-likelihood ratio method yield essentially the exact coverage probabilities, whereas the other two methods, even though they are more popular methods, yield less satisfactory results.
|Number of pages||13|
|Journal||Communications in Statistics Part B: Simulation and Computation|
|State||Published - Jan 1 2014|
Bibliographical noteFunding Information:
The first author’s research was supported in part by National Cancer Center support grant CA21765 and American Lebanese Syrian Associated Charities (ALSAC). The second author’s research was supported in part by the National Sciences and Engineering Council.
- Asymptotic theory
- Confidence interval
- Effect size
- Signed log-likelihood ratio
- Small sample
ASJC Scopus subject areas
- Statistics and Probability
- Modeling and Simulation