Related Experiment Video
Updated: Apr 26, 2026
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
Bayesian evaluation of inequality constrained hypotheses
Xin Gu1, Joris Mulder2, Maja Deković3
1Department of Methodology and Statistics.
Abstract:
Bayesian evaluation of inequality constrained hypotheses enables researchers to investigate their expectations with respect to the structure among model parameters. This article proposes an approximate Bayes procedure that can be used for the selection of the best of a set of inequality constrained hypotheses based on the Bayes factor in a very general class of statistical models. The software package BIG is provided such that psychologists can use the approach proposed for the analysis of their own data. To illustrate the approximate Bayes procedure and the use of BIG, we evaluate inequality constrained hypotheses in a path model and a logistic regression model. Two simulation studies on the performance of our approximate Bayes procedure show that it results in accurate Bayes factors.
Related Concept Videos
01:11Types of Hypothesis Testing
When the null and alternative hypotheses are stated, it is observed that the null hypothesis is a neutral statement against which the alternative hypothesis is tested. The alternative hypothesis is a claim that instead has a certain direction. If the null hypothesis claims that p = 0.5, the alternative hypothesis would be an opposing statement to this and can be put either p > 0.5, p < 0.5, or p...
01:29Application of Nonlinear Inequalities
01:28Graphical Representation of Inequalities
01:16Null and Alternative Hypotheses
The null hypothesis, denoted by H0 is a statement of no difference between the variables—they are not related. This can often be considered the status quo. As a result if you cannot accept the null, it requires some action.
The alternative hypothesis, denoted by H1 or Ha, is a claim about the...
01:16Statistical Hypothesis Testing
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
01:16Statistical 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,...