Estimating confidence regions of common measures of the baseline and treatment effect on dichotomous outcome of a population

ABSTRACT

In this article, we estimate confidence regions of the common measures of (baseline, treatment effect) in observational studies, where the measure of a baseline is baseline risk or baseline odds, while the measure of a treatment effect is odds ratio, risk difference, risk ratio or attributable fraction, and where confounding is controlled in estimation of both the baseline and treatment effect. We use only one logistic model to generate approximate distributions of the maximum-likelihood estimates of these measures and thus obtain the maximum-likelihood-based confidence regions for these measures. The method is presented via a real medical example.

KEYWORDS:

• Baseline measure
• Confidence region
• Effect measure
• Logistic model

MATHEMATICS SUBJECT CLASSIFICATION:

• 62F25
• 62E17
• 62F10

Acknowledgments

The authors are grateful to Professor Marta Granström for the data and the relevant medical information. This research received no specific grant from any funding agency in the public, commercial, or nonprofit sectors.