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Exact likelihood ratio and score confidence intervals for the binomial proportion.
Matthew C Somerville1, Rebekkah S Brown
1GlaxoSmithKline, Clinical Statistics, Research Triangle Park, NC 27709, USA. matt.c.somerville@gsk.com
Pharmaceutical Statistics
|March 9, 2013
Summary
This study evaluates exact likelihood ratio (LR) confidence intervals for binomial proportions. The exact LR method offers a reliable approach for constructing accurate confidence intervals in statistical analysis.
Area of Science:
- Statistics
- Statistical Inference
- Computational Statistics
Background:
- Numerous methods exist for calculating confidence intervals for binomial parameters, each with distinct operating characteristics.
- The exact likelihood ratio (LR) confidence interval has been proposed as a valuable method for binomial proportions.
Purpose of the Study:
- To evaluate the operating characteristics of two-sided exact LR and exact score confidence intervals for the binomial proportion.
- To compare these exact methods with other coverage-maintaining intervals (Clopper-Pearson, Blaker, Casella).
- To assess the adequacy of asymptotic approximations by comparing them with exact LR and score methods.
Main Methods:
- Evaluation of operating characteristics for exact likelihood ratio (LR) and exact score confidence intervals.
- Comparative analysis against Clopper-Pearson, Blaker, and Casella intervals.
- Comparison of exact methods with their asymptotic counterparts.
Main Results:
- The study provides a detailed comparison of the operating characteristics of various confidence interval methods for binomial proportions.
- Performance differences between exact and asymptotic methods are investigated.
- The exact LR and score intervals are assessed for their coverage properties.
Conclusions:
- The exact likelihood ratio (LR) confidence interval is a method worthy of consideration for binomial proportions.
- Understanding the operating characteristics of different confidence intervals is crucial for accurate statistical inference.
- The study contributes to the selection of appropriate methods for binomial proportion confidence interval estimation.
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