Unfortunately, in order to measure bias it is necessary to have samples for which the true relative abundances are known, such as model or mock community samples. In this chapter, we propose a ...

When the response functions are the default generalized logits, then inclusion of the keyword _RESPONSE_ in every effect in the right-hand side of the MODEL statement induces a log-linear model. The ...

In this model, the regression parameters have the interpretation in terms of the log seizure rate displayed in Table 29.6 ... These statements first produce the usual output from fitting a generalized ...

In this extreme imbalance setting, the power of the meta-analysis under inverse-variance weighting of effect sizes from the linear model (without conversion to the log-odds scale) is substantially ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...