Log-Normal Versus Gamma Models for Analyzing Data from Quality-Improvement Experiments

ABSTRACT

Recently, log-normal and gamma models are of interest in fitting data arising from quality-improvement experiments. It is known that the gamma model with the constant coefficient of variation and the log-normal model with constant variance often give similar analyzes. However, in the analysis of data from quality improvement experiments, neither the coefficient of variation nor the variance needs to be constant, so that the two models do not necessarily give similar results. A choice needs to be made between the gamma and the log-normal models.

KEYWORDS:

• joint generalized linear model
• multiplicative model
• non-constant coefficient of variation
• structured dispersion

ACKNOWLEDGEMENTS

The authors thank the referees whose comments greatly improved the article. This work was partially supported by the second stage Brain Korea 21 Project.