Bridging process-based and empirical approaches to modeling tree growth

Bridging process-based and empirical approaches to modeling tree growth.

The gulf between process-based and empirical approaches to modeling tree growth may be bridged, in part, by the use of a common model. To this end, we have formulated a process-based model of tree growth that can be fitted and applied in an empirical mode. The growth model is grounded in pipe model theory and an optimal control model of crown development. Together, the pipe model and the optima...

Theoretical and empirical review of multinomial process tree modeling.

We review a current and popular class of cognitive models called multinomial processing tree (MPT) models. MPT models are simple, substantively motivated statistical models that can be applied to categorical data. They are useful as data-analysis tools for measuring underlying or latent cognitive capacities and as simple models for representing and testing competing psychological theories. We f...

Newer Approaches to Regression and Tree-Based Modeling

Analyzing criminal trajectory profiles: Bridging multilevel and group-based approaches using growth mixture modeling

Over the last 25 years, a life-course perspective on criminal behavior has assumed increasing prominence in the literature. This theoretical development has been accompanied by changes in the statistical models used to analyze criminological data. There are two main statistical modeling techniques currently used to model longitudinal data. These are growth curve models and latent class growth m...

A Role-Based Empirical Process Modeling Environment

Much contemporary development process research is based on analyses of process steps, their duration, and the events they propagate. Our initial research in large, mature telecommunications development processes concluded that such models do not capture abstractions that remain stable over time. We turned our attention instead to empirical role-based models. The basic abstraction in the model i...