HMMTree: A computer program for latent-class hierarchical multinomial processing tree models

Latent-class hierarchical multinomial models are an important extension of the widely used family of multinomial processing tree models, in that they allow for testing the parameter homogeneity assumption and provide a framework for modeling parameter heterogeneity. In this article, the computer program HMMTree is introduced as a means of implementing latent-class hierarchical multinomial processing tree models. HMMTree computes parameter estimates, confidence intervals, and goodness-of-fit statistics for such models, as well as the Fisher information, expected category means and variances, and posterior probabilities for class membership. A brief guide to using the program is provided.

Full text: [PDF]

Download HMMTree (Windows only; Release 0.9.9.7): [Installer] [ZIP archive]

Cite HMMTree:

Stahl, C. & Klauer, K. C. (2007). HMMTree: A computer program for hierarchical multinomial processing tree models. Behavior Research Methods, 39, 267- 273.