logbin (version 1.0)

logbin-package: Relative Risk Regression Using the Log Binomial Model

Description

Methods for fitting log-link GLMs and GAMs for binomial data. The package uses EM-type algorithms with more stable convergence properties than standard methods.

Details

ll{ Package: logbin Type: Package Version: 1.0 Date: 2014-10-16 License: GPL (>= 2) } This package provides methods to fit generalized linear models (GLMs) and generalized additive models (GAMs) with log-link functions to binomial data. It has two primary functions: logbin and logbin.smooth, together with various supporting functions. It is useful in two main situations. The first is when a standard GLM routine, such as glm, fails to converge with such a model. The second is when a flexible semi-parametric component is desired in these models. One of the main purposes of this package is to provide parametric and semi-parametric adjustment of relative risks. The computational method is a combinatorial EM algorithm (Marschner, 2014), which accommodates the parameter constraints and is more stable than iteratively reweighted least squares. A collection of restricted parameter spaces is defined which covers the full parameter space, and the EM algorithm is applied within each restricted parameter space in order to find a collection of restricted maxima of the log-likelihood function, from which can be obtained the global maximum over the full parameter space. The methodology implemented in this package is presented in Marschner and Gillett (2012) and Donoghoe and Marschner (2014).

References

Donoghoe, M.W. and I.C. Marschner (2014): "Smooth semi-parametric adjustment of rate differences, risk differences and relative risks," Proceedings of the 29th International Workshop on Statistical Modelling, 1, 105--110. Marschner, I.C. and A.C. Gillett (2012): "Relative risk regression: reliable and flexible methods for log-binomial models," Biostatistics, 13, 179--192. Marschner, I.C. (2014): "Combinatorial EM algorithms," Statistics and Computing, 24, 921--940.

See Also

glm

Examples

## For examples, see example(logbin) and example(logbin.smooth)