Related Experiment Video
Updated: Feb 18, 2026

A Tactile Automated Passive-Finger Stimulator TAPS
Published on: June 3, 2009
Bayesian inference for psychology, part III: Parameter estimation in nonstandard models
Dora Matzke1, Udo Boehm2, Joachim Vandekerckhove3
1University of Amsterdam, Amsterdam, Netherlands.
Abstract:
We demonstrate the use of three popular Bayesian software packages that enable researchers to estimate parameters in a broad class of models that are commonly used in psychological research. We focus on WinBUGS, JAGS, and Stan, and show how they can be interfaced from R and MATLAB. We illustrate the use of the packages through two fully worked examples; the examples involve a simple univariate linear regression and fitting a multinomial processing tree model to data from a classic false-memory experiment. We conclude with a comparison of the strengths and weaknesses of the packages. Our example code, data, and this text are available via https://osf.io/ucmaz/ .
Related Concept Videos
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
Theory of Attribution I: Correspondent Inference Theory
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
What are Estimates?
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Distributions to Estimate Population Parameter

