Publication
Journal of Mathematical Psychology
Paper

QTEST 2.1: Quantitative testing of theories of binary choice using Bayesian inference

View publication

Abstract

This stand-alone tutorial gives an introduction to the QTEST 2.1 public domain software package for the specification and statistical analysis of certain order-constrained probabilistic choice models. Like its predecessors, QTEST 2.1 allows a user to specify a variety of probabilistic models of binary responses and to carry out state-of-the-art frequentist order-constrained hypothesis tests within a Graphical User Interface (GUI). QTEST 2.1 automatizes the mathematical characterization of so-called “random preference models”, adds some parallel computing capabilities, and, most importantly, adds tools for Bayesian inference and model selection. In this tutorial, we provide an in-depth introduction to the Bayesian features: We review order-constrained Bayesian p-values, DIC and Bayes factors, building on the data, models, and prior QTEST based frequentist data analyses of an earlier (frequentist) tutorial by Regenwetter et al. (2014).

Date

01 Aug 2019

Publication

Journal of Mathematical Psychology

Authors

Share