A Short Introduction To Recursive Partitioning

A Short Introduction to Recursive Partitioning

Analyzing Ecological Data

'Which test should I apply?' During the many years of working with ecologists, biologists and other environmental scientists, this is probably the question that the authors of this book hear the most often. The answer is always the same and along the lines of 'What are your underlying questions?', 'What do you want to show?'. The answers to these questions provide the starting point for a detailed discussion on the ecological background and purpose of the study. This then gives the basis for deciding on the most appropriate analytical approach. Therefore, a better start ing point for an ecologist is to avoid the phrase 'test' and think in terms of 'analy sis'. A test refers to something simple and unified that gives a clear answer in the form of a p-value: something rarely appropriate for ecological data. In practice, one has to apply a data exploration, check assumptions, validate the models, per haps apply a series of methods, and most importantly, interpret the results in terms of the underlying ecology and the ecological questions being investigated. Ecology is a quantitative science trying to answer difficult questions about the complex world we live in. Most ecologists are aware of these complexities, but few are fully equipped with the statistical sophistication and understanding to deal with them.

Model-Based Recursive Partitioning with Adjustment for Measurement Error

​Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning inspired recursive partitioning methods and regression models. Hanna Birke extends this approach by allowing in addition for measurement error in covariates, as frequently occurring in biometric (or econometric) studies, for instance, when measuring blood pressure or caloric intake per day. After an introduction into the background, the extended methodology is developed in detail for the Cox model and the Weibull model, carefully implemented in R, and investigated in a comprehensive simulation study.