Bayesian Statistics & Computation
Bayesian statistics - the frog example - an extended version of a student app: An introduction to Bayesian statistics
Bayesian Correlation Analysis: The "Bayesian correlation analysis" app shows how the results of Bayesian procedures vary in the light of changes regarding data and prior beliefs.
||Bayesian t-Test Teaching App: The goal of the Bayesian t-test app is to provide teachers with a handy tool to show students what a Bayes factor, and more generally, what the results from a Bayesian t-test look like when data points are added in real-time.
|P-values & Bayes factors: This app illustrates the relation between p values and Bayes factors for various widely-used statistical tests of hypotheses.
||James-Stein estimator: The goal of this shiny app is to visualize the effect of shrinkage estimators and compare their performance to other estimators.
||Sequential testing with p-values and Bayes factors This app illustrates the relation between p-values and Bayes factors for various statistical tests under sequential and block sampling procedures.
Knowledge Space Theory
|The Skill mApp aims to provide a first contact with both the Knowledge Space Theory and the skill map theory.
||Local independence: This app exemplifies the local independence assumption of the basic local independence model.
||Parameter estimation: This app uses three procedures to estimate the parameters for a data set and a knowledge structure specified by the user.
|Classical and Bayesian parameter estimation: This app demonstrates classical and Bayesian parameter estimation methods for probabilistic knowledge structures.
||Identifiability: This app visualizes the trade-off between the parameters of a non-identifiable basic local independence model (BLIM).
||Surmise Relations: This app demonstrates surmise relations and the corresponding knowledge spaces.
|Probabilistic Knowledge Assessment: This app lets you build your own knowledge structure on a set
of five items on elementary probability theory, and lets you perform a probabilistic knowledge assessment on that
structure. Especially the UI is based on a students' app.
||Deterministic Knowledge Assessment: This app lets you build your own knowledge structure on a set of five items on elementary probability theory, and lets you perform a deterministic knowledge assessment on that structure. It is derived from the
app on probabilistic knowledge assessment.
BLIM simulation: This app lets you simulate response patterns based on a given knowledge space using the BLIM.
Properties of Knowledge Spaces: This app lets you enter a knowledge structure and shows various properties of the
corresponding knowledge space.
Precedence Relation and Corresponding Quasi-Ordinal Knowledge Space: This app illustrates the one-to-one correspondence
between a precedence relation among a number of problems and a quasi-ordinal knowledge space.
Fringe & Neighbourhood: This app illustrates the fringe
and neighbourhood of knowledge states.
|Race Model: An app introducing and illustrating the race model for multisensory signals.
||TWIN: Time Window of Multisensory INtegration.
||TWIN 2017: A Shiny App for visualizing, simulating and estimating the Time-Window of INtegration (TWIN) model (version 2017).
|Comparing Intraclass Correlations for Schwarz Values across European Countries.
||Multiverse analysis: This app shows how different choices in constructing the data leads to different analysis results.