PPP: Compute Posterior Predictive P-Values

In TreeBUGS: Hierarchical Multinomial Processing Tree Modeling

Compute Posterior Predictive P-Values

Description

Computes posterior predictive p-values to test model fit.

Usage

PPP(fittedModel, M = 1000, nCPU = 4, T2 = TRUE, type = "X2")

Arguments

fittedModel	fitted latent-trait or beta MPT model (traitMPT, betaMPT)
M	number of posterior predictive samples. As a maximum, the number of posterior samples in fittedModel is used.
nCPU	number of CPUs used for parallel sampling. For large models and many participants, this requires considerable computer-memory resources (as a remedy, use nCPU=1).
T2	whether to compute T2 statistic to check coveriance structure (can take a lot of time). If some participants do not have responses for some trees, (co)variances are computed by pairwise deletion of the corresponding persons.
type	whether the T1 statistic of expected means is computed using Person's "X2" or the likelihood-ratio statistic "G2"

Author(s)

Daniel Heck

References

Klauer, K. C. (2010). Hierarchical multinomial processing tree models: A latent-trait approach. Psychometrika, 75, 70-98.

TreeBUGS documentation built on May 31, 2023, 9:21 p.m.