Overview of Generalized Linear Models
While traditional linear models are used extensively in statistical data analysis, there are types of problems for which they are not appropriate.
• It may not be reasonable to assume that data are normally distributed. For example, the normal distribution (which is continuous) may not be adequate for modeling counts or measured proportions.
• If the mean of the data is naturally restricted to a range of values, the traditional linear model may not be appropriate, since the linear predictor can take on any value. For example, the mean of a measured proportion is between 0 and 1, but the linear predictor of the mean in a traditional linear model is not restricted to this range.
• It may not be realistic ...