In this paper, we give a description of posterior predictive checking (introduced by Rubin, 1984) for detecting departures between the data and the posited model and illustrate how the posterior predictive check can be used in practice. We further discuss interpretability, frequency properties, and prior sensitivity of the posterior predictive p-value
Problem statement: Assessing the plausibility of a posited model is always fundamental in order to e...
We address the problem of assessing the fit of stochastic epidemic models to data. Two novel model a...
We define an extension of the posterior predictive $p$-value for multiple test statistics and establ...
In this paper, we give a description of posterior predictive checking (intro duced by Rubin, 1984) f...
The posterior predictive p value (ppp) was invented as a Bayesian counterpart to classical p values....
The posterior predictive distribution is the distribution of future observations, conditioned on the...
This article addresses issues of model choice in Bayesian contexts, and focusses on the use of the s...
In order to accurately control the Type I error rate (typically .05), a p value should be uniformly ...
Conditional independence (CI) between response time and response accuracy is a fundamental assumptio...
It is well-known that classical p-values sometimes behave incoherently for testing hypotheses in the...
The common practice for testing measurement invariance is to constrain parameters to be equal over g...
^aIt is well-known that classical p-values sometimes behave incoherently for testing hypotheses in ...
<p>Scatterplots of the posterior predictive distributions of (the difference between maximum and mi...
Two procedures for checking Bayesian models are compared using a simple test problem based on the lo...
The testing of two-sided hypotheses in univariate and multivariate situations is considered. The goa...
Problem statement: Assessing the plausibility of a posited model is always fundamental in order to e...
We address the problem of assessing the fit of stochastic epidemic models to data. Two novel model a...
We define an extension of the posterior predictive $p$-value for multiple test statistics and establ...
In this paper, we give a description of posterior predictive checking (intro duced by Rubin, 1984) f...
The posterior predictive p value (ppp) was invented as a Bayesian counterpart to classical p values....
The posterior predictive distribution is the distribution of future observations, conditioned on the...
This article addresses issues of model choice in Bayesian contexts, and focusses on the use of the s...
In order to accurately control the Type I error rate (typically .05), a p value should be uniformly ...
Conditional independence (CI) between response time and response accuracy is a fundamental assumptio...
It is well-known that classical p-values sometimes behave incoherently for testing hypotheses in the...
The common practice for testing measurement invariance is to constrain parameters to be equal over g...
^aIt is well-known that classical p-values sometimes behave incoherently for testing hypotheses in ...
<p>Scatterplots of the posterior predictive distributions of (the difference between maximum and mi...
Two procedures for checking Bayesian models are compared using a simple test problem based on the lo...
The testing of two-sided hypotheses in univariate and multivariate situations is considered. The goa...
Problem statement: Assessing the plausibility of a posited model is always fundamental in order to e...
We address the problem of assessing the fit of stochastic epidemic models to data. Two novel model a...
We define an extension of the posterior predictive $p$-value for multiple test statistics and establ...