QTest 2.1: quantitative testing of theories of binary choice using Bayesian inference. (English) Zbl 1426.91080
Summary: 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 M. Regenwetter et al. [“QTest: Quantitative testing of theories of binary choice”, Decis. 1, 2–34 (2014; doi:10.1037/dec0000007)].
MSC:
| 91B06 | Decision theory |
| 62P20 | Applications of statistics to economics |
| 62P15 | Applications of statistics to psychology |
Keywords:
Bayes factors; Gibbs sampler; model selection; order-constrained inference; posterior model probabilitySoftware:
QTestReferences:
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