BRPM: Bayesian Rasch Polytomous Model
In changxiulee/BayesianRasch: Bayesian Rasch Modeling

This function analyse your data using a polytomous Rasch model estimated with Bayes. Please note: 1) When your data has only two categories, the polytomous Rasch model will fall back to the dichotomous Rasch model. Therefore, both choice of model is equivalent. 2) To ensure the PCM and RSM model is identifiable, ability is assumed to be normally distributed (theta ~ N(0, 1)). 3) In RSM model, my intention is to make the andrich threshold follow the sum-to-zero constraint. However, I could not find a way to do it in JAGS. Therefore, the first andrich threshold is assumed to be 0 in JAGS. Then, the andrich threshold and beta is transformed to allow the andrich threshold to follow the sum-to-zero constraint

1	BRPM(data, item, n.chains, model = "BRSM")

`data`	A data frame with your data
`item`	Item in the data to be included in the model
`n.chains`	Number of chains for Markov Chain Monte Carlo. If you have multicores computer, you may increase the chain
`model`	Choose between 'BRSM' (Bayesian Rating Scale Model) and 'BPCM' (Bayesian Partial Credit Model). Default is set to BRSM.

Wright, B. D., & Masters, G. N. (1982). Rating scale analysis. MESA press. Kruschke, J. (2014). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. Academic Press.

changxiulee/BayesianRasch documentation built on Nov. 18, 2019, 6:54 a.m.