This paper discusses and illustrates the method of regression calibration. This is a straightforward technique for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003)....

We discuss and illustrate the method of simulation extrapolation for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). As in Hardin, Schmiediche, and Carroll (2003),...

This paper introduces additive measurement error in a generalized linear-model context. We discuss the types of measurement error along with their effects on fitted models. In addition, we present the notational conventions to be used in this and the accompanying papers. Copyright 2003 by...

This paper discusses and illustrates the qvf command for fitting generalized linear models. The differences between this new command and StataÕs glm command are highlighted. One of the most notable features of the qvf command is its ability to include instrumental variables. This functionality...

Generalized linear models (GLMs) extend linear regression to models with a non-Gaussian, or even discrete, response. GLM theory is predicated on the exponential family of distributions—a class so rich that it includes the commonly used logit, probit, and Poisson distributions. Although one can...