Stata Press is pleased to announce the release of Interpreting and Visualizing Regression Models Using Stata, Second Edition by Michael N. Mitchell.
Mitchell’s latest book is a clear treatment of how to carefully present results from model-fitting in a wide variety of settings. It is a boon to anyone who has to present the tangible meaning of a complex model clearly, regardless of the audience. Read more…
Categories: New Books, Resources, Stata Products Tags: books, contrasts, forthcoming, graphics, interaction, interpreting, linear regression, logistic regression, michael mitchell, mitchell, nonlinear, regression models, release, second, social science, Stata 16, stata press, statistics, visualizing
You have a model that is nonlinear in the parameters. Perhaps it is a model of tree growth and therefore asymptotes to a maximum value. Perhaps it is a model of serum concentrations of a drug that rise rapidly to a peak concentration and then decay exponentially. Easy enough, use nonlinear regression ([R] nl) to fit your model. But … what if you have repeated measures for each tree or repeated blood serum levels for each patient? You might want to account for the correlation within tree or patient. You might even believe that each tree has its own asymptotic growth. You need nonlinear mixed-effects models—also called nonlinear hierarchical models or nonlinear multilevel models. Read more…